Commentary: Analyzing Strategic Processing: Pros and Cons of Different Methods

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This commentary on the previous data analysis chapters lays out a number of considerations for the data analyst, beginning with the research questions to be answered. These chapters focus on traditional variable-centered analyses (e.g., ANOVA, regression), person-centered analyses—looking for subgroups of participants with similar scores on a number of variables—and qualitative analyses of think-aloud protocols and other data about the learning process. Options are summarized with the pros and cons of each, depending on results of screening for statistical assumptions, sample size, data reduction (e.g., calculating factor scores), and some measurement considerations including whether multiple measures of construct(s) are gathered. Specific assumptions, sample size, and measurement needs for different tests are noted, as are approaches that may involve less stereotyping of demographic groups. Where the data analyst has more than one option for analysis, the choice that gives the most statistical power is noted.
Original languageEnglish (US)
Title of host publicationHandbook of Strategies and Strategic Processing
EditorsDaniel L. Dinsmore, Luke K. Fryer, Meghan M. Parkinson
PublisherRoutledge
Pages393-405
Number of pages13
ISBN (Electronic)9780429752599
ISBN (Print)9781138389939
DOIs
StatePublished - Feb 6 2020

ASJC Scopus subject areas

  • Social Sciences(all)

Fingerprint Dive into the research topics of 'Commentary: Analyzing Strategic Processing: Pros and Cons of Different Methods'. Together they form a unique fingerprint.

Cite this