| Title: | Companion to Applied Regression Data Sets |
|---|---|
| Description: | Datasets to Accompany J. Fox and S. Weisberg, An R Companion to Applied Regression, Third Edition, Sage (2019). |
| Authors: | John Fox [aut, cre], Sanford Weisberg [aut], Brad Price [aut] |
| Maintainer: | John Fox <[email protected]> |
| License: | GPL (>= 2) |
| Version: | 3.0-5 |
| Built: | 2024-10-29 02:20:58 UTC |
| Source: | https://github.com/r-forge/car |
The Adler data frame has 108 rows and 3 columns.
The “experimenters” were the actual subjects of the study. They collected ratings of the apparent success of people in pictures who were pre-selected for their average appearance of success. The experimenters were told prior to collecting data that particular subjects were either high or low in their tendency to rate appearance of success, and were instructed to get good data, scientific data, or were given no such instruction. Each experimenter collected ratings from 18 randomly assigned subjects. This version of the Adler data is taken from Erickson and Nosanchuk (1977). The data described in the original source, Adler (1973), have a more complex structure.
AdlerAdler
This data frame contains the following columns:
a factor with levels:
good, good data;
none, no stress;
scientific, scientific data.
a factor with levels:
high, expect high ratings;
low, expect low ratings.
The average rating obtained.
Erickson, B. H., and Nosanchuk, T. A. (1977) Understanding Data. McGraw-Hill Ryerson.
Adler, N. E. (1973) Impact of prior sets given experimenters and subjects on the experimenter expectancy effect. Sociometry 36, 113–126.
Counts of new PhDs in the mathematical sciences for 2008-09 and 2011-12 categorized by type of institution, gender, and US citizenship status.
AMSsurveyAMSsurvey
A data frame with 24 observations on the following 5 variables.
a factor with levels I(Pu) for group I
public universities, I(Pr) for group I private universities, II
and III for groups II and III, IV for statistics and
biostatistics programs, and Va for applied mathemeatics programs.
a factor with levels Female, Male of the
recipient
a factor with levels Non-US, US giving
citizenship status
The number of individuals of each type in 2008-09
The number of individuals of each type in 2011-12
These data are produced yearly by the American Math Society.
From the now defunct http://www.ams.org/employment/surveyreports.html Supplementary Table 4 in the 2008-09 data. See http://www.ams.org/profession/data/annual-survey/docsgrtd for more recent data.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
Phipps, Polly, Maxwell, James W. and Rose, Colleen (2009), 2009 Annual Survey of the Mathematical Sciences, 57, 250–259, Supplementary Table 4, orginally downloaded from http://www.ams.org/employment/2009Survey-First-Report-Supp-Table4.pdf
The Angell data frame has 43 rows and 4 columns.
The observations are 43 U. S. cities around 1950.
AngellAngell
This data frame contains the following columns:
Moral Integration: Composite of crime rate and welfare expenditures.
Ethnic Heterogenity: From percentages of nonwhite and foreign-born white residents.
Geographic Mobility: From percentages of residents moving into and out of the city.
A factor with levels:
E Northeast;
MW Midwest;
S Southeast;
W West.
Angell, R. C. (1951) The moral integration of American Cities. American Journal of Sociology 57 (part 2), 1–140.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
The Anscombe data frame has 51 rows and 4 columns.
The observations are the U. S. states plus Washington, D. C. in 1970.
AnscombeAnscombe
This data frame contains the following columns:
Per-capita education expenditures, dollars.
Per-capita income, dollars.
Proportion under 18, per 1000.
Proportion urban, per 1000.
Anscombe, F. J. (1981) Computing in Statistical Science Through APL. Springer-Verlag.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Data on police treatment of individuals arrested in Toronto for simple possession of small quantities of marijuana. The data are part of a larger data set featured in a series of articles in the Toronto Star newspaper.
ArrestsArrests
A data frame with 5226 observations on the following 8 variables.
Whether or not the arrestee was released with a summons;
a factor with levels:
No;
Yes.
The arrestee's race; a factor with levels:
Black;
White.
1997 through 2002; a numeric vector.
in years; a numeric vector.
a factor with levels:
Female;
Male.
a factor with levels:
No;
Yes.
a factor with levels:
No;
Yes.
Number of police data bases (of previous arrests, previous convictions, parole status, etc. – 6 in all) on which the arrestee's name appeared; a numeric vector
Personal communication from Michael Friendly, York University.
summary(Arrests)summary(Arrests)
The Baumann data frame has 66 rows and 6 columns.
The data are from an experimental study conducted by Baumann and Jones, as reported
by Moore and McCabe (1993) Students were randomly assigned to one of three
experimental groups.
BaumannBaumann
This data frame contains the following columns:
Experimental group;
a factor with levels:
Basal, traditional method of teaching;
DRTA, an innovative method;
Strat, another innovative method.
First pretest.
Second pretest.
First post-test.
Second post-test.
Third post-test.
Moore, D. S. and McCabe, G. P. (1993) Introduction to the Practice of Statistics, Second Edition. Freeman, p. 794–795.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
These data are drawn from the 1997-2001 British Election Panel Study (BEPS).
BEPSBEPS
A data frame with 1525 observations on the following 10 variables.
voteParty choice: Conservative, Labour, or Liberal Democrat
agein years
economic.cond.nationalAssessment of current national economic conditions, 1 to 5.
economic.cond.householdAssessment of current household economic conditions, 1 to 5.
BlairAssessment of the Labour leader, 1 to 5.
HagueAssessment of the Conservative leader, 1 to 5.
KennedyAssessment of the leader of the Liberal Democrats, 1 to 5.
European 11-point scale that measures respondents' attitudes toward European integration. High scores represent ‘Eurosceptic’ sentiment.
political.knowledgeKnowledge of parties' positions on European integration, 0 to 3.
genderfemale or male.
J. Fox and R. Andersen (2006) Effect displays for multinomial and proportional-odds logit models. Sociological Methodology 36, 225–255.
summary(BEPS)summary(BEPS)
The Bfox data frame has 30 rows and 7 columns.
Time-series data on Canadian women's labor-force participation,
1946–1975.
BfoxBfox
This data frame contains the following columns:
Percent of adult women in the workforce.
Total fertility rate: expected births to a cohort of 1000 women at current age-specific fertility rates.
Men's average weekly wages, in constant 1935 dollars and adjusted for current tax rates.
Women's average weekly wages.
Per-capita consumer debt, in constant dollars.
Percent of the active workforce working 34 hours per week or less.
The value of tfr for 1973 is misrecorded as 2931; it should be 1931.
Fox, B. (1980) Women's Domestic Labour and their Involvement in Wage Work. Unpublished doctoral dissertation, p. 449.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
The Blackmore data frame has 945 rows and 4 columns.
Blackmore and Davis's data on exercise histories of 138 teenaged
girls hospitalized for eating disorders and 98 control subjects.
BlackmoreBlackmore
This data frame contains the following columns:
a factor with subject id codes. There are several observations for each subject, but because the girls were hospitalized at different ages, the number of cases and the age at the last case vary.
subject's age in years at the time of observation; all but the last observation for each subject were collected retrospectively at intervals of two years, starting at age 8.
the amount of exercise in which the subject engaged, expressed as estimated hours per week.
a factor with levels:
control, Control subjects;
patient, Eating-disordered patients.
Personal communication from Elizabeth Blackmore and Caroline Davis, York University.
The Burt data frame has 27 rows and 4 columns.
The “data” were simply (and notoriously) manufactured. The
same data are in the dataset “twins" in the alr3
package, but with different labels.
BurtBurt
This data frame contains the following columns:
IQ of twin raised by biological parents
IQ of twin raised by foster parents
A factor with levels (note: out of order):
high;
low;
medium.
Burt, C. (1966) The genetic determination of differences in intelligence: A study of monozygotic twins reared together and apart. British Journal of Psychology 57, 137–153.
The CanPop data frame has 16 rows and 2 columns.
Decennial time-series of Canadian population, 1851–2001.
CanPopCanPop
This data frame contains the following columns:
census year.
Population, in millions
Urquhart, M. C. and Buckley, K. A. H. (Eds.) (1965) Historical Statistics of Canada. Macmillan, p. 1369.
Canada (1994) Canada Year Book. Statistics Canada, Table 3.2.
Statistics Canada: from the now defunct http://www12.statcan.ca/english/census01/products/standard/popdwell/Table-PR.cfm.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Data are drawn from the 2011 Canadian National Election Study, including a question on banning abortion and variables related to the sampling design.
data("CES11")data("CES11")
A data frame with 2231 observations on the following 9 variables.
idHousehold ID number.
provincea factor with (alphabetical) levels AB, BC, MB, NB, NL, NS, ON, PE, QC, SK; the sample was stratified by province.
populationpopulation of the respondent's province, number over age 17.
weightweight sample to size of population, taking into account unequal sampling probabilities by province and household size.
gendera factor with levels Female, Male.
abortionattitude toward abortion, a factor with levels No, Yes; answer to the question "Should abortion be banned?"
importanceimportance of religion, a factor with (alphabetical) levels not, notvery, somewhat, very; answer to the question, "In your life, would you say that religion is very important, somewhat important, not very important, or not important at all?"
educationa factor with (alphabetical) levels bachelors (Bachelors degree), college (community college or technical school), higher (graduate degree), HS (high-school graduate), lessHS (less than high-school graduate), somePS (some post-secondary).
urbanplace of residence, a factor with levels rural, urban.
This is an extract from the data set for the 2011 Canadian National Election Study distributed by the Institute for Social Research, York University.
Fournier, P., Cutler, F., Soroka, S., and Stolle, D. (2013). Canadian Election Study 2011: Study documentation. Technical report, Canadian Opinion Research Archive, Queen's University, Kingson,Ontario.
Northrup, D. (2012). The 2011 Canadian Election Survey: Technical documention. Technical report, Institute for Social Research, York University, Toronto, Ontario.
summary(CES11)summary(CES11)
The Chile data frame has 2700 rows and 8 columns.
The data are from a national survey conducted in April and May of 1988
by FLACSO/Chile. There are some missing data.
ChileChile
This data frame contains the following columns:
A factor with levels:
C, Central;
M, Metropolitan Santiago area;
N, North;
S, South;
SA, city of Santiago.
Population size of respondent's community.
A factor with levels:
F, female;
M, male.
in years.
A factor with levels (note: out of order):
P, Primary;
PS, Post-secondary;
S, Secondary.
Monthly income, in Pesos.
Scale of support for the status-quo.
a factor with levels:
A, will abstain;
N, will vote no (against Pinochet);
U, undecided;
Y, will vote yes (for Pinochet).
Personal communication from FLACSO/Chile.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
The Chirot data frame has 32 rows and 5 columns.
The observations are counties in Romania.
ChirotChirot
This data frame contains the following columns:
Intensity of the rebellion
Commercialization of agriculture
Traditionalism
Strength of middle peasantry
Inequality of land tenure
Chirot, D. and C. Ragin (1975) The market, tradition and peasant rebellion: The case of Romania. American Sociological Review 40, 428–444 [Table 1].
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
The Cowles data frame has 1421 rows and 4 columns.
These data come from a study of the personality determinants
of volunteering for psychological research.
CowlesCowles
This data frame contains the following columns:
scale from Eysenck personality inventory
scale from Eysenck personality inventory
a factor with levels: female; male
volunteeing, a factor with levels: no; yes
Cowles, M. and C. Davis (1987) The subject matter of psychology: Volunteers. British Journal of Social Psychology 26, 97–102.
The Davis data frame has 200 rows and 5 columns.
The subjects were men and women engaged in regular exercise.
There are some missing data.
DavisDavis
This data frame contains the following columns:
A factor with levels:
F, female;
M, male.
Measured weight in kg.
Measured height in cm.
Reported weight in kg.
Reported height in cm.
Personal communication from C. Davis, Departments of Physical Education and Psychology, York University.
Davis, C. (1990) Body image and weight preoccupation: A comparison between exercising and non-exercising women. Appetite, 15, 13–21.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
The DavisThin data frame has 191 rows and 7 columns.
This is part of a larger dataset for a study of eating disorders.
The seven variables in the data frame comprise a "drive for thinness"
scale, to be formed by summing the items.
DavisThinDavisThin
This data frame contains the following columns:
a numeric vector
a numeric vector
a numeric vector
a numeric vector
a numeric vector
a numeric vector
a numeric vector
Davis, C., G. Claridge, and D. Cerullo (1997) Personality factors predisposing to weight preoccupation: A continuum approach to the association between eating disorders and personality disorders. Journal of Psychiatric Research 31, 467–480. [personal communication from the authors.]
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
Wolf depredations of livestock on Minnesota farms, 1976-1998.
DepredationsDepredations
A data frame with 434 observations on the following 5 variables.
longitudelongitude of the farm
latitudelatitude of the farm
numbernumber of depredations 1976-1998
earlynumber of depredations 1991 or before
latenumber of depredations 1992 or later
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
Harper, Elizabeth K. and Paul, William J. and Mech, L. David and Weisberg, Sanford (2008), Effectiveness of Lethal, Directed Wolf-Depredation Control in Minnesota, Journal of Wildlife Management, 72, 3, 778-784. doi:10.2193/2007-273
The Duncan data frame has 45 rows and 4 columns.
Data on the prestige and other characteristics of 45 U. S. occupations in 1950.
DuncanDuncan
This data frame contains the following columns:
Type of occupation.
A factor with the following levels:
prof, professional and managerial;
wc, white-collar;
bc, blue-collar.
Percentage of occupational incumbents in the 1950 US Census who earned $3,500 or more per year (about $36,000 in 2017 US dollars).
Percentage of occupational incumbents in 1950 who were high school graduates (which, were we cynical, we would say is roughly equivalent to a PhD in 2017)
Percentage of respondents in a social survey who rated the occupation as “good” or better in prestige
Duncan, O. D. (1961) A socioeconomic index for all occupations. In Reiss, A. J., Jr. (Ed.) Occupations and Social Status. Free Press [Table VI-1].
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
The Ericksen data frame has 66 rows and 9 columns.
The observations are 16 large cities, the remaining parts of
the states in which these cities are located, and the other
U. S. states.
EricksenEricksen
This data frame contains the following columns:
Percentage black or Hispanic.
Rate of serious crimes per 1000 population.
Percentage poor.
Percentage having difficulty speaking or writing English.
Percentage age 25 or older who had not finished highschool.
Percentage of housing in small, multiunit buildings.
A factor with levels:
city, major city;
state, state or state-remainder.
Percentage of households counted by conventional personal enumeration.
Preliminary estimate of percentage undercount.
Ericksen, E. P., Kadane, J. B. and Tukey, J. W. (1989) Adjusting the 1980 Census of Population and Housing. Journal of the American Statistical Association 84, 927–944 [Tables 7 and 8].
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
The Florida data frame has 67 rows and 11 columns.
Vote by county in Florida for President in the 2000 election.
FloridaFlorida
This data frame contains the following columns:
Number of votes for Gore
Number of votes for Bush.
Number of votes for Buchanan.
Number of votes for Nader.
Number of votes for Browne (whoever that is).
Number of votes for Hagelin (whoever that is).
Number of votes for Harris (whoever that is).
Number of votes for McReynolds (whoever that is).
Number of votes for Moorehead (whoever that is).
Number of votes for Phillips (whoever that is).
Total number of votes.
Adams, G. D. and Fastnow, C. F. (2000) A note on the voting irregularities in Palm Beach, FL. Formerly at ‘http://madison.hss.cmu.edu/’, but no longer available there.
The Freedman data frame has 110 rows and 4 columns.
The observations are U. S. metropolitan areas with 1968 populations
of 250,000 or more. There are some missing data.
FreedmanFreedman
This data frame contains the following columns:
Total 1968 population, 1000s.
Percent nonwhite population, 1960.
Population per square mile, 1968.
Crime rate per 100,000, 1969.
United States (1970) Statistical Abstract of the United States. Bureau of the Census.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
Freedman, J. (1975) Crowding and Behavior. Viking.
The Friendly data frame has 30 rows and 2 columns.
The data are from an experiment on subjects' ability to remember words
based on the presentation format.
FriendlyFriendly
This data frame contains the following columns:
A factor with levels:
Before, Recalled words presented before others;
Meshed, Recalled words meshed with others;
SFR, Standard free recall.
Number of words correctly recalled, out of 40 on final trial of the experiment.
Friendly, M. and Franklin, P. (1980) Interactive presentation in multitrial free recall. Memory and Cognition 8 265–270 [Personal communication from M. Friendly].
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
The Ginzberg data frame has 82 rows and 6 columns.
The data are for psychiatric patients hospitalized for depression.
GinzbergGinzberg
This data frame contains the following columns:
Measures subject's need to see the world in black and white.
Fatalism scale.
Beck self-report depression scale.
Adjusted Simplicity: Simplicity adjusted (by regression) for other variables thought to influence depression.
Adjusted Fatalism.
Adjusted Depression.
Personal communication from Georges Monette, Department of Mathematics and Statistics, York University, with the permission of the original investigator.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
The Greene data frame has 384 rows and 7 columns.
These are cases filed in 1990, in which refugee claimants rejected
by the Canadian Immigration and Refugee Board asked the Federal
Court of Appeal for leave to appeal the negative ruling of the Board.
GreeneGreene
This data frame contains the following columns:
Name of judge hearing case.
A factor with levels:
Desjardins, Heald, Hugessen, Iacobucci, MacGuigan,
Mahoney, Marceau, Pratte, Stone, Urie.
Nation of origin of claimant.
A factor with levels:
Argentina, Bulgaria, China, Czechoslovakia,
El.Salvador, Fiji, Ghana, Guatemala,
India, Iran, Lebanon, Nicaragua,
Nigeria, Pakistan, Poland, Somalia,
Sri.Lanka.
Judgment of independent rater.
A factor with levels:
no, case has no merit;
yes, case has some merit (leave to appeal should be granted).
Judge's decision.
A factor with levels:
no, leave to appeal not granted;
yes, leave to appeal granted.
Language of case.
A factor with levels:
English,
French.
Location of original refugee claim.
A factor with levels:
Montreal,
other,
Toronto.
Logit of success rate, for all cases from the applicant's nation.
Personal communication from Ian Greene, Department of Political Science, York University.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
This data set illustrates analyis of a multifactor observational study, with response given by subject's score on a vocabulary test, and factors for age group, education level, natality status, gender and year of the survey.
data("GSSvocab")data("GSSvocab")
A data frame with 28867 observations on the following 8 variables.
yeara factor with levels 1978 1982 1984 1987 1988 1989 1990 1991 1993 1994 1996 1998 2000 2004 2006 2008 2010 2012 2014 2016. Data are included from the GSS for each of these years.
gendera factor with levels female male
nativeBornWas the respondent born in the US? A factor with levels no and yes.
ageGroupa factor with levels 18-29 30-39 40-49 50-59 60+, grouped age of the respondent.
educGroupa factor with levels <12 yrs 12 yrs 13-15 yrs 16 yrs >16 yrs, grouped education level of the respondent. 12 years corresponds to high school graduate, 16 years to college graduate.
vocabNumber of words out of 10 correct on a vocabulary test
ageage of the respondent in years
educyears of education of the respondent
This file includes the years of the GSS for which the vocab and nativeBorn items were included.
These data were collected from the GSS data explorer https://gssdataexplorer.norc.org, using the data fields year, id_, age, educ, sex, born and wordsum. The GSS began in 1972, and has included several thousand data items, some regularly and some only once, on topics of interest to social scientists. Data have been slightly edited to change entires like No answer and Not applicable to missing value codes.
data(GSSvocab)data(GSSvocab)
The Guyer data frame has 20 rows and 3 columns.
The data are from an experiment in which four-person groups
played a prisoner's dilemma game for 30 trails, each person
making either a cooperative or competitive choice on each
trial. Choices were made either anonymously or in public;
groups were composed either of females or of males.
The observations are 20 groups.
GuyerGuyer
This data frame contains the following columns:
Number of cooperative choices (out of 120 in all).
A factor with levels:
anonymous, Anonymous choice;
public, Public choice.
Sex. A factor with levels:
female and
male.
Fox, J. and Guyer, M. (1978) Public choice and cooperation in n-person prisoner's dilemma. Journal of Conflict Resolution 22, 469–481.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2013) An R Companion to Applied Regression, Third Edition, Sage.
The Hartnagel data frame has 38 rows and 7 columns.
The data are an annual time-series from 1931 to 1968. There are
some missing data.
HartnagelHartnagel
This data frame contains the following columns:
1931–1968.
Total fertility rate per 1000 women.
Women's labor-force participation rate per 1000.
Women's post-secondary degree rate per 10,000.
Female indictable-offense conviction rate per 100,000.
Female theft conviction rate per 100,000.
Male indictable-offense conviction rate per 100,000.
Male theft conviction rate per 100,000.
The post-1948 crime rates have been adjusted to account for a difference in method of recording. Some of your results will differ in the last decimal place from those in Table 14.1 of Fox (1997) due to rounding of the data. Missing values for 1950 were interpolated.
Personal communication from T. Hartnagel, Department of Sociology, University of Alberta.
Fox, J., and Hartnagel, T. F (1979) Changing social roles and female crime in Canada: A time series analysis. Canadian Review of Sociology and Anthroplogy, 16, 96–104.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
The data comes from a unpublished master's paper by Carl Hoffstedt. They relate the automobile accident rate,
in accidents per million vehicle miles to several potential terms. The data include 39 sections of large
highways in the state of Minnesota in 1973. The goal of this analysis was to understand the impact
of design variables, Acpts, Slim, Sig, and Shld that are under the control of
the highway department, on accidents.
Highway1Highway1
This data frame contains the following columns:
1973 accident rate per million vehicle miles
length of the Highway1 segment in miles
average daily traffic count in thousands
truck volume as a percent of the total volume
(number of signalized interchanges per mile times len + 1)/len, the number of signals per mile of roadway, adjusted to have no zero values.
speed limit in 1973
width in feet of outer shoulder on the roadway
total number of lanes of traffic
number of access points per mile
number of freeway-type interchanges per mile
lane width, in feet
An indicator of the type of roadway or the source of funding for the road, either MC, FAI, PA, or MA
Carl Hoffstedt. This differs from the dataset Highway in the
alr4 package only by addition of transformation of some of the columns.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
Weisberg, S. (2014) Applied Linear Regression, Fourth Edition, Wiley, Section 7.2.
Subset of data on migraine treatments collected by Tammy Kostecki-Dillon.
KosteckiDillonKosteckiDillon
A data frame with 4152 observations on 133 subjects for the following 9 variables.
idPatient id.
timetime in days relative to the onset of treatment, which occurs at time 0.
dostime in days from the start of the study, January 1 of the first year of the study.
hatypea factor with levels Aura Mixed No Aura, the type of
migraine experienced by a subject.
ageat onset of treatment, in years.
airqa measure of air quality.
medicationa factor with levels none reduced continuing,
representing subjects who discontinued their medication, who continued but at a reduced
dose, or who continued at the previous dose.
headachea factor with levels no yes.
sexa factor with levels female male.
The data consist of headache logs kept by 133 patients in a treatment program in which bio-feedback was used to attempt to reduce migraine frequency and severity. Patients entered the program at different times over a period of about 3 years. Patients were encouraged to begin their logs four weeks before the onset of treatment and to continue for one month afterwards, but only 55 patients have data preceding the onset of treatment.
Personal communication from Georges Monette (and adapted from his description of the data).
Kostecki-Dillon, T., Monette, G., and Wong, P. (1999). Pine trees, comas, and migraines. York University Institute for Social Research Newsletter, 14:2.
summary(KosteckiDillon)summary(KosteckiDillon)
The Leinhardt data frame has 105 rows and 4 columns.
The observations are nations of the world around 1970.
LeinhardtLeinhardt
This data frame contains the following columns:
Per-capita income in U. S. dollars.
Infant-mortality rate per 1000 live births.
A factor with levels:
Africa;
Americas;
Asia, Asia and Oceania;
Europe.
Oil-exporting country.
A factor with levels:
no,
yes.
The infant-mortality rate for Jamaica is misprinted in Leinhardt and Wasserman; the correct value is given here. Some of the values given in Leinhardt and Wasserman do not appear in the original New York Times table and are of dubious validity.
Leinhardt, S. and Wasserman, S. S. (1979) Exploratory data analysis: An introduction to selected methods. In Schuessler, K. (Ed.) Sociological Methodology 1979 Jossey-Bass.
The New York Times, 28 September 1975, p. E-3, Table 3.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
A portion of an experiment to determine the limit of blank/limit of detection in a biochemical assay.
LoBDLoBD
A data frame with 84 observations on the following 9 variables.
poola factor with levels 1 2 3 4
5 6 7 8 9 10 11 12
denoting the 12 pools used in the experiment;
each pool had a different level of drug.
I1L1a numeric vector giving the measured concentration in pmol/L of drug in the assay
I1L2a numeric vector giving the measured concentration in pmol/L of drug in the assay
I2L1a numeric vector giving the measured concentration in pmol/L of drug in the assay
I2L2a numeric vector giving the measured concentration in pmol/L of drug in the assay
I3L1a numeric vector giving the measured concentration in pmol/L of drug in the assay
I3L2a numeric vector giving the measured concentration in pmol/L of drug in the assay
I4L1a numeric vector giving the measured concentration in pmol/L of drug in the assay
I4L2a numeric vector giving the measured concentration in pmol/L of drug in the assay
Important characteristics of a clinical chemistry assay are its limit of blank (LoB), and its limit of detection (LoD). The LoB, conceptually the highest reading likely to be obtained from a zero-concentration sample, is defined operationally by the upper 95% point of readings obtained from samples that do not contain the analyte. The LoD, conceptually the lowest level of analyte that can be reliably determined not to be blank, is defined operationally as true value at which there is a 95% chance of the reading being above the LoB.
These data are from a portion of a LoB/D study of an assay for a drug used to treat certain cancers. Twelve pools were used, four of them blanks of different types, and eight with successively increasing drug levels. The 8 columns of the data set refer to measurements made using different instruments I and reagent lots L.
Used as an illustrative application for Box-Cox type transformations with
negative values in Hawkins and Weisberg (2015).
For examples of its use, see bcnPower.
Hawkins, D. and Weisberg, S. (2015) Combining the Box-Cox Power and Generalized Log Transformations to Accommodate Negative Responses, submitted for publication.
LoBDLoBD
The Mandel data frame has 8 rows and 3 columns.
MandelMandel
This data frame contains the following columns:
first predictor.
second predictor.
response.
Mandel, J. (1982) Use of the singular value decomposition in regression analysis. The American Statistician 36, 15–24.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
The Migration data frame has 90 rows and 8 columns.
MigrationMigration
This data frame contains the following columns:
Province of origin (source).
A factor with levels:
ALTA, Alberta;
BC, British Columbia;
MAN, Manitoba;
NB, New Brunswick;
NFLD, New Foundland;
NS, Nova Scotia;
ONT, Ontario;
PEI, Prince Edward Island;
QUE, Quebec;
SASK, Saskatchewan.
Province of destination (1971 residence).
A factor with levels:
ALTA, Alberta;
BC, British Columbia;
MAN, Manitoba;
NB, New Brunswick;
NFLD, New Foundland;
NS, Nova Scotia;
ONT, Ontario;
PEI, Prince Edward Island;
QUE, Quebec;
SASK, Saskatchewan.
Number of migrants (from source to destination) in the period 1966–1971.
Distance (between principal cities of provinces): NFLD, St. John; PEI, Charlottetown; NS, Halifax; NB, Fredricton; QUE, Montreal; ONT, Toronto; MAN, Winnipeg; SASK, Regina; ALTA, Edmonton; BC, Vancouver.
1966 population of source province.
1971 population of source province.
1966 population of destination province.
1971 population of destination province.
There is one record in the data file for each migration stream. You can average the 1966 and 1971 population figures for each of the source and destination provinces.
Canada (1962) Map. Department of Mines and Technical Surveys.
Canada (1971) Census of Canada. Statistics Canada, Vol. 1, Part 2 [Table 32].
Canada (1972) Canada Year Book. Statistics Canada [p. 1369].
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
The Moore data frame has 45 rows and 4 columns.
The data are for subjects in a social-psychological experiment,
who were faced with manipulated disagreement from a partner of either
of low or high status. The subjects could either conform to the
partner's judgment or stick with their own judgment.
MooreMoore
This data frame contains the following columns:
Partner's status. A factor with levels:
high,
low.
Number of conforming responses in 40 critical trials.
F-Scale Categorized.
A factor with levels (note levels out of order):
high,
low,
medium.
Authoritarianism: F-Scale score.
Moore, J. C., Jr. and Krupat, E. (1971) Relationship between source status, authoritarianism and conformity in a social setting. Sociometry 34, 122–134.
Personal communication from J. Moore, Department of Sociology, York University.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
Minneapolis Demographic Data 2015, by Neighborhood, from the 2015 American Community Survey
A data frame with 84 observations on the following 7 variables.
neighborhoodname of the neighborhood
populationtotal population
blackfraction of the population estimated to be black
whitefraction of the population estimated to be white
foreignBornfraction of the population estimated to be foreign born
hhIncomeestimated median household income
povertyestimated fraction earning less than twice the poverty level
collegeGradestimated fraction with a college degree
The data frame MplsStops contains 2017 Minneapolis Police stop data, using the same neighborhood names as this data file.
http://www.mncompass.org/profiles/neighborhoods/minneapolis-saint-paul#!community-areas
str(MplsDemo)str(MplsDemo)
Results of nearly all stops made by the Minneapolis Police Department for the year 2017.
A data frame with 51857 observations on the following 14 variables.
idNumcharacter vector of incident identifiers
datea POSIXlt date variable giving the date and time of the stop
problema factor with levels suspicious for suspicious vehicle or person stops and traffic for traffic stops
citationIssueda factor with levels no yes indicating if a citation was issued
personSearcha factor with levels no yes indicating if the stopped person was searched
vehicleSearcha factor with levels no or yes indicating if a vehicle was searched
preRacea factor with levels white, black, east african, latino, native american, asian, other, unknown for the officer's assessment of race of the person stopped before speaking with the person stopped
racea factor with levels white, black, east african, latino, native american, asian, other, unknown, officer's determination of race after the incident
gendera factor with levels female, male, unknown, gender of person stopped
latlatitude of the location of the incident, somewhat rounded
longlatitude of the location of the incident, somewhat rounded
policePrecinctMinneapolis Police Precinct number
neighborhooda factor with 84 levels giving the name of the Minneapolis neighborhood of the incident
MDCa factor with levels mdc for data collected via in-vehicle computer, and other for data submitted by officers not in a vehicle, either on foot, bicycle or horseback. Several of the variables above were recorded only in-vehicle
A few stops have been deleted, either because thesu location data was missing, or a few very rare categories were also removed. The data frame MplsDemo contains 2015 demongraphic data on Minneapolis neighborhoods, using the same neighborhood names as this data file. Demographics are available for 84 of Minneaolis' 87 neighborhoods. The remaining 3 presumably have no housing.
These are public data obtained from <http://opendata.minneapolismn.gov/datasets/police-stop-data>. A few more fields, and more data, are available at the original source
summary(MplsStops)summary(MplsStops)
The Mroz data frame has 753 rows and 8 columns.
The observations, from the Panel Study of Income Dynamics (PSID),
are married women.
MrozMroz
This data frame contains the following columns:
labor-force participation; a factor with levels:
no;
yes.
number of children 5 years old or younger.
number of children 6 to 18 years old.
in years.
wife's college attendance; a factor with levels:
no;
yes.
husband's college attendance; a factor with levels:
no;
yes.
log expected wage rate; for women in the labor force, the actual
wage rate; for women not in the labor force, an imputed value based on the
regression of lwg on the other variables.
family income exclusive of wife's income.
Mroz, T. A. (1987) The sensitivity of an empirical model of married women's hours of work to economic and statistical assumptions. Econometrica 55, 765–799.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. (2000) Multiple and Generalized Nonparametric Regression. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
Long. J. S. (1997) Regression Models for Categorical and Limited Dependent Variables. Sage.
These contrived repeated-measures data are taken from O'Brien and Kaiser (1985). The data are from an imaginary study in which 16 female and male subjects, who are divided into three treatments, are measured at a pretest, postest, and a follow-up session; during each session, they are measured at five occasions at intervals of one hour. The design, therefore, has two between-subject and two within-subject factors.
The contrasts for the treatment factor are set to and
. The contrasts for the gender factor are set to
contr.sum.
OBrienKaiserOBrienKaiser
A data frame with 16 observations on the following 17 variables.
treatmenta factor with levels control A B
gendera factor with levels F M
pre.1pretest, hour 1
pre.2pretest, hour 2
pre.3pretest, hour 3
pre.4pretest, hour 4
pre.5pretest, hour 5
post.1posttest, hour 1
post.2posttest, hour 2
post.3posttest, hour 3
post.4posttest, hour 4
post.5posttest, hour 5
fup.1follow-up, hour 1
fup.2follow-up, hour 2
fup.3follow-up, hour 3
fup.4follow-up, hour 4
fup.5follow-up, hour 5
O'Brien, R. G., and Kaiser, M. K. (1985) MANOVA method for analyzing repeated measures designs: An extensive primer. Psychological Bulletin 97, 316–333, Table 7.
OBrienKaiser contrasts(OBrienKaiser$treatment) contrasts(OBrienKaiser$gender)OBrienKaiser contrasts(OBrienKaiser$treatment) contrasts(OBrienKaiser$gender)
Contrived repeated-measures data from O'Brien and Kaiser (1985). For details see OBrienKaiser, which is for the "wide" form of the same data.
OBrienKaiserLongOBrienKaiserLong
A data frame with 240 observations on the following 6 variables.
treatmenta between-subjects factor with levels control, A, B.
gendera between-subjects factor with levels F, M.
scorethe numeric response variable.
idthe subject id number.
phasea within-subjects factor with levels pre, post, fup.
houra within-subjects factor with levels 1, 2, 3, 4, 5.
O'Brien, R. G., and Kaiser, M. K. (1985) MANOVA method for analyzing repeated measures designs: An extensive primer. Psychological Bulletin 97, 316–333, Table 7.
head(OBrienKaiserLong, 15) # first subjecthead(OBrienKaiserLong, 15) # first subject
The Ornstein data frame has 248 rows and 4 columns.
The observations are the 248 largest Canadian firms with
publicly available information in the mid-1970s. The names
of the firms were not available.
OrnsteinOrnstein
This data frame contains the following columns:
Assets in millions of dollars.
Industrial sector.
A factor with levels:
AGR, agriculture, food, light industry;
BNK, banking;
CON, construction;
FIN, other financial;
HLD, holding companies;
MAN, heavy manufacturing;
MER, merchandizing;
MIN, mining, metals, etc.;
TRN, transport;
WOD, wood and paper.
Nation of control.
A factor with levels:
CAN, Canada;
OTH, other foreign;
UK, Britain;
US, United States.
Number of interlocking director and executive positions shared with other major firms.
Ornstein, M. (1976) The boards and executives of the largest Canadian corporations. Canadian Journal of Sociology 1, 411–437.
Personal communication from M. Ornstein, Department of Sociology, York University.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
The data give the chemical composition of ancient pottery found at four sites in Great Britain. They appear in Hand, et al. (1994), and are used to illustrate MANOVA in the SAS Manual. (Suggested by Michael Friendly.)
PotteryPottery
A data frame with 26 observations on the following 6 variables.
Sitea factor with levels AshleyRails Caldicot IsleThorns Llanedyrn
AlAluminum
FeIron
MgMagnesium
CaCalcium
NaSodium
Hand, D. J., Daly, F., Lunn, A. D., McConway, K. J., and E., O. (1994) A Handbook of Small Data Sets. Chapman and Hall.
PotteryPottery
The Prestige data frame has 102 rows and 6 columns.
The observations are occupations.
PrestigePrestige
This data frame contains the following columns:
Average education of occupational incumbents, years, in 1971.
Average income of incumbents, dollars, in 1971.
Percentage of incumbents who are women.
Pineo-Porter prestige score for occupation, from a social survey conducted in the mid-1960s.
Canadian Census occupational code.
Type of occupation.
A factor with levels (note: out of order):
bc, Blue Collar;
prof, Professional, Managerial, and Technical;
wc, White Collar.
Canada (1971) Census of Canada. Vol. 3, Part 6. Statistics Canada [pp. 19-1–19-21].
Personal communication from B. Blishen, W. Carroll, and C. Moore, Departments of Sociology, York University and University of Victoria.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
The Quartet data frame has 11 rows and 5 columns.
These are contrived data.
QuartetQuartet
This data frame contains the following columns:
X-values for datasets 1–3.
Y-values for dataset 1.
Y-values for dataset 2.
Y-values for dataset 3.
X-values for dataset 4.
Y-values for dataset 4.
Anscombe, F. J. (1973) Graphs in statistical analysis. American Statistician 27, 17–21.
The Robey data frame has 50 rows and 3 columns.
The observations are developing nations around 1990.
RobeyRobey
This data frame contains the following columns:
A factor with levels:
Africa;
Asia, Asia and Pacific;
Latin.Amer, Latin America and Caribbean;
Near.East, Near East and North Africa.
Total fertility rate (children per woman).
Percent of contraceptors among married women of childbearing age.
Robey, B., Shea, M. A., Rutstein, O. and Morris, L. (1992) The reproductive revolution: New survey findings. Population Reports. Technical Report M-11.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
This data set is originally from Rossi et al. (1980), and is used as an example in Allison (1995). The data pertain to 432 convicts who were released from Maryland state prisons in the 1970s and who were followed up for one year after release. Half the released convicts were assigned at random to an experimental treatment in which they were given financial aid; half did not receive aid.
RossiRossi
A data frame with 432 observations on the following 62 variables.
weekweek of first arrest after release or censoring; all censored observations are censored at 52 weeks.
arrest1 if arrested, 0 if not arrested.
finfinancial aid: no yes.
agein years at time of release.
raceblack or other.
wexpfull-time work experience before incarceration: no or yes.
marmarital status at time of release: married or not married.
paroreleased on parole? no or yes.
prionumber of convictions prior to current incarceration.
educlevel of education: 2 = 6th grade or less;
3 = 7th to 9th grade; 4 = 10th to 11th grade;
5 = 12th grade; 6 = some college.
emp1employment status in the first week after release: no or yes.
emp2as above.
emp3as above.
emp4as above.
emp5as above.
emp6as above.
emp7as above.
emp8as above.
emp9as above.
emp10as above.
emp11as above.
emp12as above.
emp13as above.
emp14as above.
emp15as above.
emp16as above.
emp17as above.
emp18as above.
emp19as above.
emp20as above.
emp21as above.
emp22as above.
emp23as above.
emp24as above.
emp25as above.
emp26as above.
emp27as above.
emp28as above.
emp29as above.
emp30as above.
emp31as above.
emp32as above.
emp33as above.
emp34as above.
emp35as above.
emp36as above.
emp37as above.
emp38as above.
emp39as above.
emp40as above.
emp41as above.
emp42as above.
emp43as above.
emp44as above.
emp45as above.
emp46as above.
emp47as above.
emp48as above.
emp49as above.
emp50as above.
emp51as above.
emp52as above.
Allison, P.D. (1995). Survival Analysis Using the SAS System: A Practical Guide. Cary, NC: SAS Institute.
Rossi, P.H., R.A. Berk, and K.J. Lenihan (1980). Money, Work, and Crime: Some Experimental Results. New York: Academic Press.
John Fox, Marilia Sa Carvalho (2012). The RcmdrPlugin.survival Package: Extending the R Commander Interface to Survival Analysis. Journal of Statistical Software, 49(7), 1-32.
summary(Rossi)summary(Rossi)
The Sahlins data frame has 20 rows and 2 columns.
The observations are households in a Central African village.
SahlinsSahlins
This data frame contains the following columns:
Consumers/Gardener, ratio of consumers to productive individuals.
Acres/Gardener, amount of land cultivated per gardener.
Sahlins, M. (1972) Stone Age Economics. Aldine [Table 3.1].
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
The 2008-09 nine-month academic salary for Assistant Professors, Associate Professors and Professors in a college in the U.S. The data were collected as part of the on-going effort of the college's administration to monitor salary differences between male and female faculty members.
SalariesSalaries
A data frame with 397 observations on the following 6 variables.
ranka factor with levels AssocProf AsstProf Prof
disciplinea factor with levels A (“theoretical” departments)
or B (“applied” departments).
yrs.since.phdyears since PhD.
yrs.serviceyears of service.
sexa factor with levels Female Male
salarynine-month salary, in dollars.
Fox J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
The SLID data frame has 7425 rows and 5 columns.
The data are from the 1994 wave of the Canadian Survey of Labour and Income Dynamics,
for the province of Ontario.
There are missing data, particularly for wages.
SLIDSLID
This data frame contains the following columns:
Composite hourly wage rate from all jobs.
Number of years of schooling.
in years.
A factor with levels:
Female,
Male.
A factor with levels:
English,
French,
Other.
The data are taken from the public-use dataset made available by Statistics Canada, and prepared by the Institute for Social Research, York University.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
Soil characteristics were measured on samples from three types of contours (Top, Slope, and Depression) and at four depths (0-10cm, 10-30cm, 30-60cm, and 60-90cm). The area was divided into 4 blocks, in a randomized block design. (Suggested by Michael Friendly.)
SoilsSoils
A data frame with 48 observations on the following 14 variables. There are 3 factors and 9 response variables.
Groupa factor with 12 levels, corresponding to the combinations of Contour and Depth
Contoura factor with 3 levels: Depression Slope Top
Deptha factor with 4 levels: 0-10 10-30 30-60 60-90
Gpa factor with 12 levels, giving abbreviations for the groups:
D0 D1 D3 D6 S0 S1 S3 S6 T0 T1 T3 T6
Blocka factor with levels 1 2 3 4
pHsoil pH
Ntotal nitrogen in %
Densbulk density in gm/cm$^3$
Ptotal phosphorous in ppm
Cacalcium in me/100 gm.
Mgmagnesium in me/100 gm.
Kphosphorous in me/100 gm.
Nasodium in me/100 gm.
Conducconductivity
These data provide good examples of MANOVA and canonical discriminant analysis in a somewhat
complex multivariate setting. They may be treated as a one-way design (ignoring Block),
by using either Group or Gp as the factor, or a two-way randomized block
design using Block, Contour and Depth (quantitative, so orthogonal
polynomial contrasts are useful).
Horton, I. F.,Russell, J. S., and Moore, A. W. (1968) Multivariate-covariance and canonical analysis: A method for selecting the most effective discriminators in a multivariate situation. Biometrics 24, 845–858. Originally from ‘http://www.stat.lsu.edu/faculty/moser/exst7037/soils.sas’ but no longer available there.
Khattree, R., and Naik, D. N. (2000) Multivariate Data Reduction and Discrimination with SAS Software. SAS Institute.
Friendly, M. (2006) Data ellipses, HE plots and reduced-rank displays for multivariate linear models: SAS software and examples. Journal of Statistical Software, 17(6), doi:10.18637/jss.v017.i06.
The States data frame has 51 rows and 8 columns.
The observations are the U. S. states and Washington, D. C.
StatesStates
This data frame contains the following columns:
U. S. Census regions.
A factor with levels:
ENC, East North Central;
ESC, East South Central;
MA, Mid-Atlantic;
MTN, Mountain;
NE, New England;
PAC, Pacific;
SA, South Atlantic;
WNC, West North Central;
WSC, West South Central.
Population: in 1,000s.
Average score of graduating high-school students in the state on the verbal component of the Scholastic Aptitude Test (a standard university admission exam).
Average score of graduating high-school students in the state on the math component of the Scholastic Aptitude Test.
Percentage of graduating high-school students in the state who took the SAT exam.
State spending on public education, in \$1000s per student.
Average teacher's salary in the state, in $1000s.
United States (1992) Statistical Abstract of the United States. Bureau of the Census.
Moore, D. (1995) The Basic Practice of Statistics. Freeman, Table 2.1.
Information on the survival status, sex, age, and passenger class of 1309 passengers in the Titanic disaster of 1912.
TitanicSurvivalTitanicSurvival
A data frame with 1309 observations on the following 4 variables.
survivedno or yes.
sexfemale or male
agein years (and for some children, fractions of a year); age is missing for 263 of the passengers.
passengerClass1st, 2nd, or 3rd class.
This is part of a larger data set compiled by Thomas Cason. Many additional details are given in the sources cited below.
Data set titanic3 from the now defunct
http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/DataSets.
https://www.encyclopedia-titanica.org/
F. E. Harrell, Jr. (2001) Regression Modeling Strategies New York: Springer.
summary(TitanicSurvival)summary(TitanicSurvival)
Data on transaction times in branch offices of a large Australian bank.
TransactTransact
This data frame contains the following columns:
number of type 1 transactions
number of type 2 transactions
total transaction time, minutes
Cunningham, R. and Heathcote, C. (1989), Estimating a non-Gaussian regression model with multicollinearity. Australian Journal of Statistics, 31,12-17.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
Weisberg, S. (2014) Applied Linear Regression, Fourth Edition, Wiley, Section 4.6.1.
National health, welfare, and education statistics for 213 places, mostly UN members, but also other areas like Hong Kong that are not independent countries.
data(UN)data(UN)
A data frame with 213 rows on the following 7 variables.
regionRegion of the world: Africa, Asia, Caribbean, Europe,
Latin Amer, North America, NorthAtlantic, Oceania.
groupA factor with levels oecd for countries that
are members of the OECD, the Organization for Economic Co-operation and
Development, as of May 2012, africa for countries on the African
continent, and other for all other countries. No OECD countries are
located in Africa.
fertilityTotal fertility rate, number of children per woman.
ppgdpPer capita gross domestic product in US dollars.
lifeExpFFemale life expectancy, years.
pctUrbanPercent urban.
infantMortalityInfant deaths by age 1 year per 1000 live births
Similar data, from the period 2000-2003, appear in the alr3 package
under the name UN3.
This data set was formerly named UNlla and replaces the older dataset named UN.
All data were collected from UN tables accessed at http://unstats.un.org/unsd/demographic/products/socind/ on April 23, 2012. OECD membership is from https://www.oecd.org/, accessed May 25, 2012.
Weisberg, S. (2014). Applied Linear Regression, 4th edition. Hoboken NJ: Wiley.
summary(UN)summary(UN)
Social indicators data on 207 nations distributed by the United Nations circa 1998.
data("UN98")data("UN98")
A data frame with 207 observations on the following 13 variables.
regiona factor with alphabetical levels Africa, America, Asia, Europe, Oceania.
tfrtotal fertility rate, number of children per woman.
contraceptionpercentage of married women using any method of contraception.
educationMaleaverage number of years of education for men.
educationFemaleaverage number of years of education for women.
lifeMaleexpectation of life at birth for males.
lifeFemaleexpectation of life at birth for females.
infantMortalityinfant deaths per 1000 live births.
GDPperCapitagross domestic product per person in U.S. dollars.
economicActivityMalepercentage of men who are economically active.
economicActivityFemalepercentage of women who are economically active.
illiteracyMalepercentage of males 15 years of age and older who are illiterate.
illiteracyFemalepercentage of females 15 years of age and older who are illiterate.
In a few cases where the percentages of males and females 15 and older who are illiterate were unavailable, these variables were filled in by regression imputation from the corresponding percentages 25 and older who are illiterate.
Downloaded from http://www.un.org/Depts/unsd/social/main.htm in 1998.
summary(UN98)summary(UN98)
The USPop data frame has 22 rows and 1 columns.
This is a decennial time-series, from 1790 to 2000.
USPopUSPop
This data frame contains the following columns:
census year.
Population in millions.
U.S.~Census Bureau: https://www.census-charts.com/Population/pop-us-1790-2000.html, downloaded 1 May 2008.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
The Vocab data frame has 30,351 rows and 4 columns.
The observations are respondents to U.S. General Social Surveys, 1972-2016.
VocabVocab
This data frame contains the following columns:
Year of the survey.
Sex of the respondent, Female or Male.
Education, in years.
Vocabulary test score: number correct on a 10-word test.
National Opinion Research Center General Social Survey. GSS Cumulative Datafile 1972-2016, downloaded from http://gss.norc.org/.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
Contrived data on weight loss and self esteem over three months, for three groups of individuals: Control, Diet and Diet + Exercise. The data constitute a double-multivariate design.
WeightLossWeightLoss
A data frame with 34 observations on the following 7 variables.
groupa factor with levels Control Diet DietEx.
wl1Weight loss at 1 month
wl2Weight loss at 2 months
wl3Weight loss at 3 months
se1Self esteem at 1 month
se2Self esteem at 2 months
se3Self esteem at 3 months
Helmert contrasts are assigned to group, comparing Control vs. (Diet DietEx)
and Diet vs. DietEx.
Originally taken from http://www.csun.edu/~ata20315/psy524/main.htm, but modified slightly. Courtesy of Michael Friendly.
Data on whether or not households in Bangladesh changed the wells that they were using.
WellsWells
A data frame with 3020 observations on the following 5 variables.
switchwhether or not the household switched to
another well from an unsafe well: no or yes.
arsenicthe level of arsenic contamination in the household's original well, in hundreds of micrograms per liter; all are above 0.5, which was the level identified as “safe”.
distancein meters to the closest known safe well.
educationin years of the head of the household.
associationwhether or not any members of the household
participated in any community organizations: no or yes.
The data are for an area of Arahazar upazila, Bangladesh. The researchers labelled each well with its level of arsenic and an indication of whether the well was “safe” or “unsafe.” Those using unsafe wells were encouraged to switch. After several years, it was determined whether each household using an unsafe well had changed its well. These data are used by Gelman and Hill (2007) for a logistic-regression example.
http://www.stat.columbia.edu/~gelman/arm/examples/arsenic/wells.dat.
A. Gelman and J. Hill (2007) Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge: Cambridge University Press.
summary(Wells)summary(Wells)
The Womenlf data frame has 263 rows and 4 columns.
The data are from a 1977 survey of the Canadian population.
WomenlfWomenlf
This data frame contains the following columns:
Labour-Force Participation.
A factor with levels (note: out of order):
fulltime, Working full-time;
not.work, Not working outside the home;
parttime, Working part-time.
Husband's income, $1000s.
Presence of children in the household.
A factor with levels:
absent,
present.
A factor with levels:
Atlantic, Atlantic Canada;
BC, British Columbia;
Ontario;
Prairie, Prairie provinces;
Quebec.
Social Change in Canada Project. York Institute for Social Research.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
The Wong data frame has 331 row and 7 columns. The observations are longitudinal
data on recovery of IQ after comas of varying duration for 200 subjects.
WongWong
This data frame contains the following columns:
idpatient ID number.
daysnumber of days post coma at which IQs were measured.
durationduration of the coma in days.
sexa factor with levels Female and Male.
agein years at the time of injury.
piqperformance (i.e., mathematical) IQ.
viqverbal IQ.
The data are from Wong, Monette, and Weiner (2001) and are for 200 patients who sustained traumatic brain injuries resulting in comas of varying duration. After awakening from their comas, patients were periodically administered a standard IQ test, but the average number of measurements per patient is small (331/200 = 1.7).
Wong, P. P., Monette, G., and Weiner, N. I. (2001) Mathematical models of cognitive recovery. Brain Injury, 15, 519–530.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
summary(Wong)summary(Wong)
This is a three-factor experiment with each factor at three levels, for a total of 27 runs. Samples of worsted yarn were with different levels of the three factors were given a cyclic load until the sample failed. The goal is to understand how cycles to failure depends on the factors.
WoolWool
This data frame contains the following columns:
length of specimen (250, 300, 350 mm)
amplitude of loading cycle (8, 9, 10 min)
load (40, 45, 50g)
number of cycles until failure
Box, G. E. P. and Cox, D. R. (1964). An analysis of transformations (with discussion). J. Royal Statist. Soc., B26, 211-46.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
Weisberg, S. (2014) Applied Linear Regression, Fourth Edition, Wiley, Section 6.3.
Data from the World Values Surveys 1995-1997 for Australia, Norway, Sweden, and the United States.
WVSWVS
A data frame with 5381 observations on the following 6 variables.
poverty“Do you think that what the government is doing for people in poverty in
this country is about the right amount, too much, or too little?” (ordered):
Too Little, About Right, Too Much
.
religionMember of a religion: no or yes.
degreeHeld a university degree: no or yes.
countryAustralia, Norway, Sweden, or USA.
agein years.
gendermale or female.
J. Fox and R. Andersen (2006) Effect displays for multinomial and proportional-odds logit models. Sociological Methodology 36, 225–255.
summary(WVS)summary(WVS)