Psyc 480 -- Dr. King

ANCOVA Practice Problems

Answer the questions at the end of each problem.

1) tresselt.txt
# James Tresselt, Psyc 497, Fall 1995
# Most of these data were obtained from the Office of Institutional
# Research at Coastal Carolina University and are from a random
# sample of freshman who were admitted in Fall 1990 and who were
# still present at the end of Spring 1991. Variables are:
#   Gender: Female/Male
#   SATV: SAT Verbal Score
#   SATQ: SAT Quantitative Score
#   SATT: SAT Total = SATV + SATQ
#   GPA91: college GPA at the end of Spring semester 1991
#   HSGPA: high school grade point average (James did not get this
#          from OIR; they gave him class rank; I have made up GPAs
#          to replace these in a way that I thought was reasonable)
#   orient: did the student attend freshman orientation? (I made
#           this up out of thin air; 0=no, 1=yes)
#   sex: a dummy coded version of Gender (0=Female, 1=Male)

file = "http://ww2.coastal.edu/kingw/psyc480/data/tresselt.txt"
tres = read.table(header=T, stringsAsFactors=T, file=file)
summary(tres)

Do the same analysis that we did previously with tresselt3.txt, except this time
use HSGPA as the covariate instead of SATT.

Question 1: Why did the effect of Gender disappear (p=0.176) when HSGPA was added
to the model as a covariate?

2) pse.txt
# Data from Mike Milne PSYC 497 project Spring 2006, who wanted to find out
# if overall self-esteem and physical self-efficacy are related. Variables:
#     CSEI: score on the Coopersmith Self-Esteem Inventory
#     pse: score on a physical self efficacy scale
#     gender: 1(male), 2(female)
# A correlation matrix tells the story: r.crit = .182. Is the relationship
# different for men vs. women?

file = "http://ww2.coastal.edu/kingw/psyc480/data/pse.txt"
milne = read.table(header=T, stringsAsFactors=T, file=file)
summary(milne)

As a researcher, it is your job in observational research to think of potential
confounds and control them or remove them. Mike Milne (Psyc 497, SP 2006) did
so in his research in which he was looking at gender differences in physical
self-efficacy. (If you have some sort of physical task you must do, do you feel
that you're up to it?) Physical self-efficacy is surely correlated with general
self-esteem, and we are not interested in general self-esteem and want it taken
out of the PSE dependent variable.

summary(aov(pse~CSEI,data=milne))
summary(aov(pse~gender,data=milne))
summary(aov(pse~CSEI+gender,data=milne))

Question 2: Did the effect of CSEI change when gender was added to the model
as a categorical IV? Why not? Did the effect of gender change when CSEI was
added to the model as a covariate? Why? Why did it change in the direction
in which it did?

3) ptsd.txt
# These data are those obtained by Rodriguez, N., Ryan, S. W., Vande
# Kemp, H., & Foy, D. W. (1997). Posttraumatic stress disorder in adult female
# survivors of childhood sexual abuse: A comparison study. Journal of Counseling
# and Clinical Psychology, 65, 53-59.
# Variables:
#    cpa - childhood physical abuse measured by a standardized assessment device
#    ptsd - adult posttraumatic stress disorder measured by a standardized
#           assessment device
#    csa - childhood sexual abuse (Abused/NotAbused)
# Question under investigation: In this sample, is PTSD a function of CPA, of
# CSA, or of both?

file = "http://ww2.coastal.edu/kingw/psyc480/data/ptsd.txt"
my.data = read.table(header=T, stringsAsFactors=T, file=file)
summary(my.data)

t.test(ptsd~csa, data=my.data, var.eq=T)
summary(lm(ptsd~cpa+csa, data=my.data))

Question 3: Did the effect of csa change when cpa was added to the model as
a covariate? Why?