Model Misspecification and Assumption Violations With the Linear Mixed Model: A Meta-Analysis

LeBeau, Brandon; Song, Yoon Ah; Liu, Wei Cheng

doi:10.1177/2158244018820380

Cited by 12 publications

(9 citation statements)

References 31 publications

(45 reference statements)

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“…Person-mean-centered state extraversion was used as a Level 1 predictor of momentary mood. Level 2 random intercepts and random slopes were included in the model (LeBeau et al, 2018 ). To test whether the two experimental conditions differed in their association between state extraversion and momentary mood, we additionally included the cross-level interaction between sampling frequency at the person level and state extraversion at the questionnaire level.…”

Section: Methodsmentioning

confidence: 99%

The effects of assessment intensity on participant burden, compliance, within-person variance, and within-person relationships in ambulatory assessment

2021

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Considering the very large number of studies that have applied ambulatory assessment (AA) in the last decade across diverse fields of research, knowledge about the effects that these design choices have on participants’ perceived burden, data quantity (i.e., compliance with the AA protocol), and data quality (e.g., within-person relationships between time-varying variables) is surprisingly restricted. The aim of the current research was to experimentally manipulate aspects of an AA study’s assessment intensity—sampling frequency (Study 1) and questionnaire length (Study 2)—and to investigate their impact on perceived burden, compliance, within-person variability, and within-person relationships between time-varying variables. In Study 1, students (n = 313) received either 3 or 9 questionnaires per day for the first 7 days of the study. In Study 2, students (n = 282) received either a 33- or 82-item questionnaire three times a day for 14 days. Within-person variability and within-person relationships were investigated with respect to momentary pleasant-unpleasant mood and state extraversion. The results of Study 1 showed that a higher sampling frequency increased perceived burden but did not affect the other aspects we investigated. In Study 2, longer questionnaire length did not affect perceived burden or compliance but yielded a smaller degree of within-person variability in momentary mood (but not in state extraversion) and a smaller within-person relationship between state extraversion and mood. Differences between Studies 1 and 2 with respect to the type of manipulation of assessment intensity are discussed.

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Section: Methodsmentioning

confidence: 99%

The effects of assessment intensity on participant burden, compliance, within-person variance, and within-person relationships in ambulatory assessment

2021

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“…We did not model random slopes due to convergence issues resulting from small variances of the slopes across people. If there is variation in the slopes across people (i.e., the variance of the slopes across people does not equal 0 in the population), prior simulation evidence indicates that the fixed effect estimates will be unbiased (Kwok, West, & Green, 2007; LeBeau, 2016), however, the standard errors for the linear slope may be biased, resulting in inflated Type I errors (LeBeau, 2018; LeBeau, Song, & Liu, 2018). Because the primary interest in this study was the direction and magnitude of the slope estimates (rather than tests of whether the slopes differed reliably from 0), we deemed this approach satisfactory.…”

Section: Methodsmentioning

confidence: 99%

Creating a Developmental Scale to Account for Heterotypic Continuity in Development: A Simulation Study

2020

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Many psychological constructs show heterotypic continuity—their behavioral manifestations change with development but their meaning remains the same. However, research has paid little attention to how to account for heterotypic continuity. A promising approach to account for heterotypic continuity is creating a developmental scale using vertical scaling. A simulation was conducted to compare creating a developmental scale using vertical scaling to traditional approaches of longitudinal assessment. Traditional approaches that failed to account for heterotypic continuity resulted in less accurate growth estimates, at the person‐ and group level. Findings suggest that ignoring heterotypic continuity may result in faulty developmental inferences. Creating a developmental scale with vertical scaling is recommended to link different measures across time and account for heterotypic continuity.

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“…4 and Additional file 1: Figs. S6-S8) [24][25][26]. rmRNAseq, which uses a CAR covariance structure, remains overly conservative with noticeably lower sensitivity in most scenarios, although FDR inflation is seen for between-subject and interaction tests at the smallest sample size ( N = 3 per group).…”

Section: Error Rates and Sensitivitymentioning

confidence: 99%

lmerSeq: an R package for analyzing transformed RNA-Seq data with linear mixed effects models

2022

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Background Studies that utilize RNA Sequencing (RNA-Seq) in conjunction with designs that introduce dependence between observations (e.g. longitudinal sampling) require specialized analysis tools to accommodate this additional complexity. This R package contains a set of utilities to fit linear mixed effects models to transformed RNA-Seq counts that properly account for this dependence when performing statistical analyses. Results In a simulation study comparing lmerSeq and two existing methodologies that also work with transformed RNA-Seq counts, we found that lmerSeq was comprehensively better in terms of nominal error rate control and statistical power. Conclusions Existing R packages for analyzing transformed RNA-Seq data with linear mixed models are limited in the variance structures they allow and/or the transformation methods they support. The lmerSeq package offers more flexibility in both of these areas and gave substantially better results in our simulations.

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Model Misspecification and Assumption Violations With the Linear Mixed Model: A Meta-Analysis

Cited by 12 publications

References 31 publications

The effects of assessment intensity on participant burden, compliance, within-person variance, and within-person relationships in ambulatory assessment

The effects of assessment intensity on participant burden, compliance, within-person variance, and within-person relationships in ambulatory assessment

Creating a Developmental Scale to Account for Heterotypic Continuity in Development: A Simulation Study

lmerSeq: an R package for analyzing transformed RNA-Seq data with linear mixed effects models

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