Research Methods & Data Analysis in I-O Psychology Flashcards
7 cards from real SIOP practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Research Methods & Data Analysis in I-O Psychology flashcards as text
Which of the following best describes the purpose of bootstrapping in mediation analysis?
Answer: To estimate the sampling distribution of the indirect effect without assuming normality
Bootstrapping resamples the data repeatedly to construct an empirical sampling distribution for the indirect effect, providing more accurate confidence intervals.
A moderator variable in a regression context is indicated by:
Answer: A significant interaction term between predictor and moderator
Moderation is evidenced by a significant interaction term, indicating that the predictor-outcome relationship differs across levels of the moderator.
An organization collects supervisor ratings and subordinate self-ratings of performance. The low correlation between them is best explained by:
Answer: Rater perspective differences and unique information
Supervisors and subordinates observe different behaviors and have access to different information, which typically produces low convergence.
What is the key statistical assumption underlying the use of parametric tests like ANOVA and t-tests?
Answer: Data are drawn from normally distributed populations
Parametric tests assume that the data come from populations with normal distributions, though they are robust to moderate violations with large samples.
Which approach to handling missing data is generally superior to listwise deletion when data are missing at random (MAR)?
Answer: Multiple imputation
Multiple imputation creates several plausible datasets reflecting uncertainty about missing values, yielding unbiased estimates under the MAR assumption.
A researcher conducting an organizational survey finds that employees in the same department have more similar responses than employees across departments. Which analysis is most appropriate?
Answer: Multilevel modeling (HLM)
Multilevel modeling accounts for the non-independence of observations nested within groups such as departments or teams.
Which of the following is a key difference between exploratory factor analysis (EFA) and confirmatory factor analysis (CFA)?
Answer: CFA tests a pre-specified factor structure while EFA generates one from data
CFA tests whether data fit a theoretically specified factor structure, while EFA is data-driven and uncovers factor patterns without prior constraints.