Middle school students' willingness to engage in activities with peers with ADHD symptoms: A multiple indicators multiple causes (MIMIC) model

Ogg, Julia A.; McMahan, Melanie M.; Dedrick, Robert F.; Mendez, Linda Raffaele

doi:10.1016/j.jsp.2013.01.002

Cited by 5 publications

(7 citation statements)

References 35 publications

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“…The inclusion of a set of covariates provides the MIMIC model with important extra information in addition to the measurement model (Chen, 1981; Cheng, Shao, & Lathrop, 2016; Muthén, 1989). The MIMIC model has been utilized extensively by applied researchers, especially for testing latent factor means or the regression effect from a grouping variable on the latent factor (Condon, 2010; Ogg, McMahan, Dedrick, & Mendez, 2013; Thompson & Green, 2006). When modeling the effects of multiple covariates on the latent factor in the MIMIC model, the interactions between the covariates should be investigated in addition to the main effects of the covariates.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Test of Covariate Moderation Effects in Multilevel MIMIC Models

Cao

Kim

Chen

et al. 2018

Educational and Psychological Measurement

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In multilevel multiple-indicator multiple-cause (MIMIC) models, covariates can interact at the within level, at the between level, or across levels. This study examines the performance of multilevel MIMIC models in estimating and detecting the interaction effect of two covariates through a simulation and provides an empirical demonstration of modeling the interaction in multilevel MIMIC models. The design factors include the location of the interaction effect (i.e., between, within, or across levels), cluster number, cluster size, intraclass correlation (ICC) level, magnitude of the interaction effect, and cross-level measurement invariance status. Type I error, power, relative bias, and root mean square of error of the interaction effects are examined. The results showed that multilevel MIMIC models performed well in detecting the interaction effect at the within or across levels. However, when the interaction effect was at the between level, the performance of multilevel MIMIC models depended on the magnitude of the interaction effect, ICC, and sample size, especially cluster number. Overall, cross-level measurement noninvariance did not make a notable impact on the estimation of interaction in the structural part of multilevel MIMIC models when factor loadings were allowed to be different across levels.

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Section: Introductionmentioning

confidence: 99%

Exploring the Test of Covariate Moderation Effects in Multilevel MIMIC Models

Cao

Kim

Chen

et al. 2018

Educational and Psychological Measurement

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“…In line with previous literature (McMahan, 2011;Swords et al, 2011), the degree to which children were willing to engage with Anon differed across activities and vignette conditions. Children reported being more likely to engage with Anon in active/recreational and social activities than academic activities, supporting Ogg et al (2013).…”

Section: Discussionmentioning

confidence: 65%

The effect of social devaluation, labeling, and familiarity on children's attitudes and behavioral intentions toward a peer with symptoms of ADHD

Greenway

Robinson

King

2023

Psychology in the Schools

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The present study examined the attitudes and behavioral intentions of 336 children aged 7–11 toward a hypothetical peer with symptoms of attention‐deficit hyperactivity disorder (ADHD) to determine whether they were influenced by labeling, social devaluation, or familiarity. Children read one of five vignettes describing the behavior of a gender‐neutral peer before completing self‐report measures of attitudes and behavioral intentions. Results showed children held predominantly negative attitudes toward the hypothetical peer, which were more pronounced for inattentive than hyperactive/impulsive symptoms. These findings suggest that children were more likely to devalue internalizing rather than externalizing behaviors. Children also reported being more likely to engage in active/recreational and social activities rather than academic activities. In addition, the diagnostic label “ADHD” led to more negative attitudes and behavioral intentions, while knowing someone with ADHD mediated the negative effect of hyperactive/impulsive symptoms on attitudes and behavioral intentions. Finally, significant positive relationships were found between attitudes and children's willingness to engage in social, academic, and physical activities. Policy and practice implications of these findings are discussed.

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“…Oort’s correction adjusts the critical chi-square value to account for potential model misspecification in the full-invariance baseline model and was found to control Type I error rates at or below the nominal level (it also compared favorably to Bonferroni corrections) and to maintain high power across different study conditions in a recent simulation study from Kim et al (2012). An application of this adjustment procedure is provided in Ogg, McMahan, Dedrick, and Mendez (2013).…”

Section: Resultsmentioning

confidence: 99%

“…Oort's correction adjusts the critical chi-square value to account for potential model misspecification in the full-invariance baseline model and was found to control Type I error rates at or below the nominal level (it also compared favorably to Bonferroni corrections) and to maintain high power across different study conditions in a recent simulation study from Kim et al (2012). An application of this adjustment procedure is provided in Ogg, McMahan, Dedrick, and Mendez (2013). 3 Although there is no firm rule for discriminant validity pertaining to CFA model tests, correlations with other latent factors Ͻ.7 are frequently accepted as evidence of discriminant validity; correlations Ͼ.85 are usually viewed as problematic because they are indicative of some redundancy of the latent factors (Brown, 2006;Kline, 2011).…”

Section: Mimic Modelsmentioning

confidence: 99%

DISC Predictive Scales (DPS): Factor structure and uniform differential item functioning across gender and three racial/ethnic groups for ADHD, conduct disorder, and oppositional defiant disorder symptoms.

Wiesner

Windle

Kanouse

et al. 2015

Psychological Assessment

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The factor structure and potential uniform differential item functioning (DIF) among gender and three racial/ethnic groups of adolescents (African American, Latino, White) were evaluated for attention deficit/hyperactivity disorder (ADHD), conduct disorder (CD), and oppositional defiant disorder (ODD) symptom scores of the DISC Predictive Scales (DPS; Leung et al., 2005; Lucas et al., 2001). Primary caregivers reported on DSM–IV ADHD, CD, and ODD symptoms for a probability sample of 4,491 children from three geographical regions who took part in the Healthy Passages study (mean age = 12.60 years, SD = 0.66). Confirmatory factor analysis indicated that the expected 3-factor structure was tenable for the data. Multiple indicators multiple causes (MIMIC) modeling revealed uniform DIF for three ADHD and 9 ODD item scores, but not for any of the CD item scores. Uniform DIF was observed predominantly as a function of child race/ethnicity, but minimally as a function of child gender. On the positive side, uniform DIF had little impact on latent mean differences of ADHD, CD, and ODD symptomatology among gender and racial/ethnic groups. Implications of the findings for researchers and practitioners are discussed.

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Middle school students' willingness to engage in activities with peers with ADHD symptoms: A multiple indicators multiple causes (MIMIC) model

Cited by 5 publications

References 35 publications

Exploring the Test of Covariate Moderation Effects in Multilevel MIMIC Models

Exploring the Test of Covariate Moderation Effects in Multilevel MIMIC Models

The effect of social devaluation, labeling, and familiarity on children's attitudes and behavioral intentions toward a peer with symptoms of ADHD

DISC Predictive Scales (DPS): Factor structure and uniform differential item functioning across gender and three racial/ethnic groups for ADHD, conduct disorder, and oppositional defiant disorder symptoms.

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