Sample size determination for constrained longitudinal data analysis

2009 ◽  
Vol 28 (4) ◽  
pp. 679-699 ◽  
Author(s):  
Kaifeng Lu ◽  
Devan V. Mehrotra ◽  
Guanghan Liu
2017 ◽  
Author(s):  
John Kitchener Sakaluk ◽  
Stephen David Short

Sexuality researchers frequently use exploratory factor analysis (EFA), in order to illuminate the distinguishable theoretical constructs assessed by a set of variables. EFA entails a substantive number of analytic decisions to be made with respect to sample size determination, and how factors are extracted, rotated, and retained. The available analytic options, however, are not all equally empirically rigorous. In the present paper, we discuss the commonly available options for conducting EFA, and which constitute best practices for EFA. We also present the results of a methodological review of the analytic options for EFA used by sexuality researchers in over 200 EFAs, published in more than 160 articles and chapters from 1974 to 2014. Our review reveals that best practices for EFA are actually those least frequently used by sexuality researchers. We introduce freely available analytic resources to help make it easier for sexuality researchers to adhere to best practices when conducting EFAs in their own research.


2017 ◽  
Author(s):  
Matthew McBee ◽  
Matthew Makel ◽  
Scott J. Peters ◽  
Michael S. Matthews

The ruinous consequences of currently accepted practices in study design and data analysis have revealed themselves in the low reproducibility of findings in fields such as psychology, medicine, biology, and economics. Because giftedness research relies on the same underlying statistical and sociological paradigms, it is likely that our field also suffers from poor reproducibility and unreliable literature. This paper describes open science practices that will increase the rigor and trustworthiness of gifted education’s scientific processes and their associated findings: open data; open materials; and preregistration of hypotheses, design, sample size determination, and statistical analysis plans. Readers are directed to internet resources for facilitating open science.


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