Chapter Nine: Multigroup Design Flashcards
Chi-Square Test of Independence
A statistical test in which both variables are categorical. This test generally examines if the distribution of participants across categories is different from what would happen if there were no difference between the groups
Confound
A variable that the researcher unintentionally varies along with the manipulation
Empty Control Group
A group that does not receive any form of the treatment and just completes the dependent variable
Exploratory Analyses
Statistical tests that examine potential differences that were not anticipated or predicted prior to conducting the study
Hypothesis-Guessing
When a participant in a study actively attempts to identify the purpose of the research
Methodological Pluralism
The use of multiple methods or strategies to answer a research question
Multigroup Design
An experimental design with three or more groups
Nonlinear (or functional) relationships
Any association between variables that the use of just two comparison groups cannot uncover. These relationships, often identified on a graph as a curved or curvilinear line, help provide us with a clearer picture of how variables relate to one another
One-Way Analysis of Variance (One-Way ANOVA)
A statistical test that determines whether responses from the different conditions are essentially the same or whether the responses from at least one of the conditions differ from the others
Placebo Group
A group where participants believe they are getting the treatment, but in reality they are not
Planned Contrasts
Statistical tests that examine comparisons between groups that were predicted ahead of time. These test have the added benefit of allowing the comparison of combined conditions to other conditions in the study
Post-Hoc Tests
Statistical tests that examine all possible combinations of conditions in a way that statistically accounts for the fact that not all of them were predicted ahead of time
Power
A study’s ability to find differences between groups when there is a real difference (i.e., when the null hypothesis is false); the probability that a study will yield significant results