Statistical power analysis and sample size planning for moderated mediation models

Xu, Ziqian; Gao, Fei; Fa, Anqi; Qu, Wen; Zhang, Zhiyong

doi:10.3758/s13428-024-02342-2

Cited by 13 publications

(1 citation statement)

References 24 publications

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“…Based on our planned statistical analyses, we calculated the required sample size. In view of the fact that there seemed not a completely suitable estimation method in a two-stage moderated mediation model ( 35 ), we refer to previous studies and utilized the Monte Carlo Power Analysis for Indirect Effects technique developed by Schoemann et al ( 36 ) to determine the minimum sample size needed for this study. With guidance from correlations and standard deviations from previous studies ( 5 , 37 , 38 ), and assuming 80% power in a two-stage mediation model, we calculated a minimum requirement of 650 participants.…”

Section: Measures and Methodsmentioning

confidence: 99%

What can we learn about stress and sleep from COVID-19 pandemic—perspective from the theory of preventive stress management

Liu,

Liang,

et al. 2024

Front. Public Health

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BackgroundThe COVID-19 pandemic has presented unique challenges to individuals worldwide, with a significant focus on the impact on sleep. However, the precise mechanisms through which emotional and cognitive variables mediate this relationship remain unclear. To expand our comprehensive understanding of variables, the present study utilizes the Preventive Stress Management theory, to test the relationship between perceived social support and sleep quality, as well as the effect of perceived COVID-19 stress, hope, negative emotions and coping styles.MethodsData were collected in March 2022 from 1,034 college students in two universities located in Liaoning Province, China, using an online survey platform regarding perceived social support, perceived COVID-19 stress, sleep quality, hope, negative emotions and coping styles. The moderated mediation model were conducted using Process macro program (Model 6) and the syntax in SPSS.ResultsThe results revealed perceived COVID-19 stress and negative emotions sequentially mediated the negative relationship between perceived social support and sleep quality. Furthermore, hope and coping styles were found to moderate the sequential mediating effect.ConclusionThe present study sheds light on the pathways that affect sleep quality among college students during the COVID-19 pandemic. Findings highlight the protective roles played by positive social and personal resources, such as perceived social support, hope, and effective coping styles, against sleep problems. These insights have important implications for the development of targeted interventions to improve sleep outcomes during this challenging time.

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