CHS 627: Multivariate Methods in Health Statistics
Review/Preview:
Predictors, Outcomes, Null Hypotheses, and Statistical Tests
 
Univariate
(no or one predictor)
Multivariate
(two or more predictors)
 
UNIVARIATE
Number and type of predictor variables
Type of outcome
Null Hypothesis (H0)
Test(s)
 no predictor variable
normal
one-sample t-test
non-normal
one-sample median/
sign test
categorical
one-sample z-test for proportions
binomial test
 Chi-square goodness-of-fit test
no predictors,
no outcomes
(i.e., looking for association or independence among 2 or more variables)
normal
Pearson correlation
 
factor analysis
one or more non-normal
Spearman rank correlation
categorical
contingency coefficient
odds ratio
one categorical predictor
(2 categories)
normal
two independent sample t-test
(if independent groups or random assignment to groups)
paired t-test
(if matched samples or repeated measures)
non-normal
Mann-Whitney Wilcoxon rank sum test
(if independent groups or random assignment to groups)
Wilcoxon signed ranks test
(if matched samples or repeated measures)
categorical
Chi-square test
(if independent groups or random assignment to groups)
McNemar chi-square test
(if matched samples or repeated measures)
 one categorical predictor
(3 or more categories)
 normal
Oneway ANOVA
(if independent groups or random assignment to groups)
Repeated Measures ANOVA
(if matched samples or repeated measures)
 non-normal
 Kruskal-Wallis test
(if independent samples or random assignment to groups)
categorical
Chi-square test
(if independent samples or random assignment to groups)
one continuous predictor
normal
simple linear regression
 non-normal
transformation
categorical
logistic regression

 
MULTIVARIATE
One outcome,
two or more predictors
Number and type of predictor variables
Type of outcome
Null Hypothesis (H0)
Test(s)
 2 or more categorical predictors
(2 or more categories each)
 normal
Factorial ANOVA
(if independent groups or random assignment to groups)
 non-normal
 
 transformation
categorical
log-linear analysis
2 or more continuous predictors
normal
multiple linear regression
non-normal
transformation
 categorical
 logistic regression
mixture of categorical and continuous predictors
normal
analysis of covariance (ANCOVA)
general linear model
non-normal
transformation
categorical
logistic regression
Two or more outcomes,
one or more predictors
Type of predictor variable(s)
Type of outcome
Test
categorical
normal
multivariate analysis of variance
(MANOVA)
continuous
multivariate multiple regression
mixed categorical and continuous
multivariate general linear model


Page editor is Julia Hartman.

Last modified November 29, 2000.
The information in this site is current through August 15, 2000.
Although the authors of this Web site have made every reasonable effort to be factually accurate, no responsibility is assumed for editorial or clerical errors or error occasioned by honest mistake. All information contained on this Web site is subject to change by the appropriate officials of The University of Alabama without prior notice. Material on this Web site does not serve as a contract between The University of Alabama and any other party.