OpenMx: An Open Source Extended Structural Equation Modeling Framework

Boker, Steven M.; Neale, Michael C.; Maes, Hermine H.; Wilde, Michael; Spiegel, Michael; Brick, Timothy R.; Spies, Jeffrey R.; Estabrook, Ryne; Kenny, Sarah; Bates, Timothy C.; Mehta, Paras; Fox, John

doi:10.1007/s11336-010-9200-6

Cited by 1,044 publications

(951 citation statements)

References 12 publications

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“…Post-hoc analysis was performed, including sex as a covariate in the models. Analyses were performed using OpenMx software (Boker et al, 2011), and the polychoric and tetrachoric correlations were calculated using the polychor and psych package, all run within the R environment (R-Development- Core-Team, 2010).…”

Section: Resultsmentioning

confidence: 99%

The Covariation Between Burnout and Sick Leave Due to Mental Disorders Is Explained by a Shared Genetic Liability: A Prospective Swedish Twin Study With a Five-Year Follow-up

et al. 2014

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Background: This study aims to assess whether the associations between burnout and sick leave due to stress-related mental disorders, other mental disorders, and somatic conditions are influenced by familial (genetic and shared environmental) factors. Methods: In this prospective cohort study, 23,611 Swedish twins born between 1959 and 1985, who answered a web-based questionnaire, including the Pines Burnout Measure 2004-2006, were included. Registry data on sick leave spells from the response date until December 31, 2010 were obtained from the Swedish Social Insurance Agency. Logistic regression analysis was performed to assess odds ratios with 95% confidence intervals for the association between burnout and sick leave for the whole sample, while conditional logistic regression of the same-sex discordant twin pairs was used to estimate the association between burnout and sick leave, adjusting for familial confounding. The Bivariate Cholesky models were used to assess whether the covariation between burnout and sick leave was explained by common genetic and/or shared environmental factors. Results: Burnout was a risk factor for sick leave due to stress-related and other mental disorders, and these associations were explained by familial factors. The phenotypic correlation between burnout and sick leave due to somatic conditions was 0.07 and the association was not influenced by familial factors. The phenotypic correlations between burnout and sick leave due to stress-related (0.26) and other mental disorders (0.30) were completely explained by common genetic factors. Conclusions: The association between burnout and sick leave due to stress-related and other mental disorders seems to be a reflection of a shared genetic liability.

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Section: Resultsmentioning

confidence: 99%

The Covariation Between Burnout and Sick Leave Due to Mental Disorders Is Explained by a Shared Genetic Liability: A Prospective Swedish Twin Study With a Five-Year Follow-up

et al. 2014

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“…Prior to estimating heritability, maximum likelihood analyses were conducted to test assumptions regarding the homogeneity of means, variances, and covariances using OpenMx (Boker et al, 2011). As darker hair color is correlated with thicker diameter, hair color was included as a covariate in all analyses, as well as sex, age, and ancestry in terms of Northern European versus Southern European descent.…”

Section: Methodsmentioning

confidence: 99%

Variation and Heritability in Hair Diameter and Curvature in an Australian Twin Sample

Brims²,

McNevin

et al. 2016

Twin Res Hum Genet

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Hair diameter and curvature are two characteristics of human scalp hair used in forensic contexts. While previous data show that subjective categorization of hair curvature is highly heritable, the heritability of objectively measured curvature and diameter, and variability of hair characteristics within each individual have not yet been studied. The present study measured hair diameter and curvature using an optical fiber diameter analyzer in a sample of 2,332 twins and siblings. Heritability was estimated using maximum likelihood structural equation modeling. Results show sex differences in the magnitude of genetic influence for mean diameter and curvature, with the vast majority of the variance accounted for by genetic effects in males (diameter = 86%, curvature = 53%) and females (diameter = 77%, curvature = 61%). The consistency of diameter (variance within an individual) was also highly heritable, but did not show sex limitation, with 68% of the variance accounted for by genetic factors. Moderate phenotypic correlations were seen between diameter and consistency (r = 0.3) but there was little correlation between diameter and curvature (r = -0.13). A bivariate Cholesky analysis was used to estimate the genetic and environmental correlations between hair diameter and consistency, yielding genetic correlations of r gF = 0.27 for females and r gM = 0.25 for males.

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“…Intra-class correlations of height, weight and BMI were computed for the total number of MZ and DZ twin pairs included in the study and five zygosity-by-sex groups (MZ-boys, MZ-girls, DZ-boys, DZ-girls, DZ-opposite-sex) respectively. Then, classical twin models were used to test for different models and to quantify the magnitude of the genetic and environmental influences on variations in the body measures using the OpenMx package (Boker et al, 2011) in the R software (http://www.r-project.org; Ihaka & Gentleman, 1996). However, three important assumptions were made: (1) trait relevant environments are similar to the same extent in MZ and DZ twin pairs; (2) mating occurs randomly in the population; and (3) no interaction or correlation between genes and environment (Elston, 2012).…”

Section: Statistical Analysesmentioning

confidence: 99%

Genetic and Environmental Effects on Weight, Height, and BMI Under 18 Years in a Chinese Population-Based Twin Sample

et al. 2015

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This study examined the genetic and environmental effects on variances in weight, height, and body mass index (BMI) under 18 years in a population-based sample from China. We selected 6,644 monozygotic and 5,969 dizygotic twin pairs from the Chinese National Twin Registry (CNTR) aged under 18 years (n = 12,613). Classic twin analyses with sex limitation were used to estimate the genetic and environmental components of weight, height, and BMI in six age groups. Sex-limitation of genetic and shared environmental effects was observed, especially when puberty begins. Heritability for weight, height, and BMI was low at 0-2 years old (less than 20% for both sexes) but increased over time, accounting for half or more of the variance in the 15-17 year age group for boys. For girls, heritabilities for weight, height and BMI was maintained at approximately 30% after puberty. Common environmental effects on all body measures were high for girls (59-87%) and presented a small peak during puberty. Genetics appear to play an increasingly important role in explaining the variation in weight, height, and BMI from early childhood to late adolescence, particularly in boys. Common environmental factors exert their strongest and most independent influence specifically in the pre-adolescent period and more significantly in girls. These findings emphasize the need to target family and social environmental interventions in early childhood years, especially for females. Further studies about puberty-related genes and social environment are needed to clarify the mechanism of sex differences.

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OpenMx: An Open Source Extended Structural Equation Modeling Framework

Cited by 1,044 publications

References 12 publications

The Covariation Between Burnout and Sick Leave Due to Mental Disorders Is Explained by a Shared Genetic Liability: A Prospective Swedish Twin Study With a Five-Year Follow-up

The Covariation Between Burnout and Sick Leave Due to Mental Disorders Is Explained by a Shared Genetic Liability: A Prospective Swedish Twin Study With a Five-Year Follow-up

Variation and Heritability in Hair Diameter and Curvature in an Australian Twin Sample

Genetic and Environmental Effects on Weight, Height, and BMI Under 18 Years in a Chinese Population-Based Twin Sample

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