Differential effects of formative feedback on math achievement and
                        their predictors: Application of regression mixture analysis

This study aims to provide an empirical demonstration of a novel method, regression mixture model, by examining differential effects of somatic amplification to positive affect and identifying the predictors that contribute to the differential effects. Data derived from the second wave of Midlife in the United States. The analytic sample consisted of 1,766 adults aged from 33 to 84 years. Regression mixture models were fitted using Mplus 7.4, and a two-step model-building approach was adopted. Three latent groups were identified consisting of a maladaptive (32.1%), a vulnerable (62.5%), and a resilient (5.4%) group. Six covariates (i.e., age, education level, positive relations with others, purpose in life, depressive symptoms, and physical health) significantly predicted the latent class membership in the regression mixture model. The study demonstrated the regression mixture model to be a flexible and efficient statistical tool in assessing individual differences in response to adversity and identifying resilience factors, which contributes to aging research.

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Children exposed to intimate partner violence: Identifying differential effects of family environment on children's trauma and psychopathology symptoms through regression mixture models

Child Abuse & Neglect ◽

10.1016/j.chiabu.2016.06.010 ◽

2016 ◽

Vol 58 ◽

pp. 1-11 ◽

Cited By ~ 15

Author(s):

Shelby Elaine McDonald ◽

Sunny Shin ◽

Rosalie Corona ◽

Anna Maternick ◽

Sandra A. Graham-Bermann ◽

...

Keyword(s):

Intimate Partner Violence ◽

Mixture Models ◽

Family Environment ◽

Partner Violence ◽

Intimate Partner ◽

Differential Effects ◽

Regression Mixture Models ◽

Psychopathology Symptoms ◽

Regression Mixture

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Self-Regulatory Climate: A Social Resource for Student Regulation and Achievement

Teachers College Record ◽

10.1177/016146811511700207 ◽

2015 ◽

Vol 117 (2) ◽

pp. 1-28 ◽

Cited By ~ 3

Author(s):

Curt M. Adams ◽

Patrick B. Forsyth ◽

Ellen Dollarhide ◽

Ryan Miskell ◽

Jordan Ware

Keyword(s):

Math Achievement ◽

Self Regulation ◽

Psychological Needs ◽

School Level ◽

Differential Effects ◽

Self Regulated Learning ◽

Regulatory Climate ◽

Ex Post ◽

Regulated Learning ◽

The Relationship

Background/Context Schools have differential effects on student learning and development, but research has not generated much explanatory evidence of the social-psychological pathway to better achievement outcomes. Explanatory evidence of how normative conditions enable students to thrive is particularly relevant in the urban context where attention disproportionately centers on the pathology of these environments rather than social attributes that contribute to student growth. Research Purpose Our purpose in this study was to determine if a self-regulatory climate works through student self-regulation to influence academic achievement. We hypothesized that (1) self-regulatory climate explains school-level differences in self-regulated learning, and (2) self-regulated learning mediates the relationship between self-regulatory climate and math achievement. Research Design We used ex post facto survey data from students and teachers in 80 elementary and secondary schools from a large, southwestern urban school district. A multilevel modeling building process in HLM 7.0 was used to test our hypotheses. Results Both hypotheses were supported. Self-regulatory climate explained significant school-level variance in self-regulated learning. Additionally, student self-regulated learning mediated the relationship between self-regulatory climate and math achievement. Conclusions Our results suggest that schools, like teachers, have differential effects on the motivational resources of students, with self-regulatory climate being an essential social condition for self-regulation and achievement. We believe self-regulatory climate has value for educators seeking to provide equitable learning opportunities for all students and for researchers seeking to account for achievement differences attributed to schools. In both cases, self-regulatory climate advances a construct and measure that conceptualizes and operationalizes school-level support for psychological needs.

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