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menbreg command  (STATA Corporation)


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    STATA Corporation menbreg command
    Menbreg Command, supplied by STATA Corporation, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/menbreg+command/menbreg+command/pmc12057091-167-29-33
    Average 90 stars, based on 1 article reviews
    menbreg command - by Bioz Stars, 2026-10
    90/100 stars

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    Article Title: Circulation of DENV-2 serotype associated with increased risk of cumulative incidence of severe dengue and dengue with warning signs: A 16-year retrospective study in Peru
    Article Snippet: Given that our outcome variable had overdispersion, we used mixed negative binomial regression models for repeated measures over time [ ] to estimate crude and adjusted cumulative incidence ratios (IRR) using the “menbreg” command in Stata (versión 17.0, StataCorp LLC, College Station, TX), for this we also evaluated multicollinearity among the predictors.

    Article Title: Geographic Distribution of Central Nervous System Rehabilitation Treatment in Korea and Its Associated Factors
    Article Snippet: To consider both the correlation of outcomes over time and overdispersion, we used multiple random intercept negative binomial regression using the menbreg command in STATA (Stata Corp., College Station, TX, USA).

    Article Title: Age, Period and Cohort Effects On Alcohol Consumption In Estonia, 1996-2018.
    Article Snippet: Aims: To analyse the independent effects of age, period and cohort on estimated daily alcohol consumption in Estonia.. Methods: This study used data from nationally representative repeated cross-sectional surveys from 1996 to 2018 and included 11,717 men and 16,513 women aged 16–64 years in total.. The dependent variables were consumption of total alcohol and consumption by types of beverages (beer, wine and strong liquor) presented as average daily consumption in grams of absolute alcohol.

    Article Title: Geographic Distribution of Central Nervous System Rehabilitation Treatment in Korea and Its Associated Factors.
    Article Snippet: To consider both the correlation of outcomes over time and overdispersion, we used multiple random intercept negative binomial regression using the menbreg command in STATA (Stata Corp., College Station, TX, USA).25 Results from the association analyses are presented as a rate ratio (RR) with 95% confidence intervals (CIs).

    Article Title: Risk factors associated with zero-dose and under-immunized children, and the number of vaccination doses received by children in Ethiopia: a negative binomial regression analysis
    Article Snippet: A random-intercept negative binomial model (Model 2) was then fitted to estimate associations between individual- and community-level independent variables and the number of vaccine doses received, using the ‘ menbreg ’ command in Stata.

    Article Title: Community correlates of change: A mixed-effects assessment of shooting dynamics during COVID-19
    Article Snippet: All models were run using the menbreg command in Stata v17.0.

    Article Title: County-level Predictors of Coronavirus Disease 2019 (COVID-19) Cases and Deaths in the United States: What Happened, and Where Do We Go from Here?
    Article Snippet: Using the menbreg command in Stata version 14.0 (StataCorp LLC, College Station, TX), we fit negative binomial mixed-effects regression models (which allow for overdispersion) [ ] to estimate county-level predictors of cumulative rates of COVID-19 cases and deaths.

    Article Title: County-level vaccination coverage and rates of COVID-19 cases and deaths in the United States: An ecological analysis
    Article Snippet: Using the menbreg command in Stata version 14.0 (StataCorp LLC, College Station, Texas), we fit negative binomial regression models (which allow for overdispersion) to estimate the relationship between county-level vaccine coverage and cumulative rates of COVID-19 cases and deaths controlling for differences in county-level environmental, sociodemographic, economic, and health-status-related characteristics.



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    menbreg command  (STATA Corporation)
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    menbreg command with the aghq  (STATA Corporation)
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    Estimates of the mean-structure coefficients of the two-level model for the different software implementations and the 9112 genes, for which the model was successfully fitted for all the implementations. The densities of the estimates are shown along the diagonal. The lower triangle contains Bland–Altman plots of the estimates for pairs of different software implementations, with the red dashed line indicating the mean difference and the black dashed lines marking the 95% limits of agreement. The upper triangle presents the numerical values of the limits. Panel A: β 1 ; Panel B: β 2 ; Panel C: β 3 . LME4L — lme4 with the Laplace approximation; LME4A — lme4 with the <t>AGHQ</t> approximation; GLMMa — GLMMadaptive ; TMB — glmmTMB ; SAS — PROC NLMIXED ; STATA <t>—</t> <t>menbreg</t> .
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    menbreg command function  (STATA Corporation)
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    STATA Corporation menbreg command function
    Estimates of the mean-structure coefficients of the two-level model for the different software implementations and the 9112 genes, for which the model was successfully fitted for all the implementations. The densities of the estimates are shown along the diagonal. The lower triangle contains Bland–Altman plots of the estimates for pairs of different software implementations, with the red dashed line indicating the mean difference and the black dashed lines marking the 95% limits of agreement. The upper triangle presents the numerical values of the limits. Panel A: β 1 ; Panel B: β 2 ; Panel C: β 3 . LME4L — lme4 with the Laplace approximation; LME4A — lme4 with the <t>AGHQ</t> approximation; GLMMa — GLMMadaptive ; TMB — glmmTMB ; SAS — PROC NLMIXED ; STATA <t>—</t> <t>menbreg</t> .
    Menbreg Command Function, supplied by STATA Corporation, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/menbreg+command/menbreg+command/10__1111_slash_radm__12605-240-2-6
    Average 90 stars, based on 1 article reviews
    menbreg command function - by Bioz Stars, 2026-10
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    Estimates of the mean-structure coefficients of the two-level model for the different software implementations and the 9112 genes, for which the model was successfully fitted for all the implementations. The densities of the estimates are shown along the diagonal. The lower triangle contains Bland–Altman plots of the estimates for pairs of different software implementations, with the red dashed line indicating the mean difference and the black dashed lines marking the 95% limits of agreement. The upper triangle presents the numerical values of the limits. Panel A: β 1 ; Panel B: β 2 ; Panel C: β 3 . LME4L — lme4 with the Laplace approximation; LME4A — lme4 with the AGHQ approximation; GLMMa — GLMMadaptive ; TMB — glmmTMB ; SAS — PROC NLMIXED ; STATA — menbreg .

    Journal: Bioinformatics Advances

    Article Title: A hierarchical negative-binomial model for analysis of correlated sequencing data: practical implementations

    doi: 10.1093/bioadv/vbaf126

    Figure Lengend Snippet: Estimates of the mean-structure coefficients of the two-level model for the different software implementations and the 9112 genes, for which the model was successfully fitted for all the implementations. The densities of the estimates are shown along the diagonal. The lower triangle contains Bland–Altman plots of the estimates for pairs of different software implementations, with the red dashed line indicating the mean difference and the black dashed lines marking the 95% limits of agreement. The upper triangle presents the numerical values of the limits. Panel A: β 1 ; Panel B: β 2 ; Panel C: β 3 . LME4L — lme4 with the Laplace approximation; LME4A — lme4 with the AGHQ approximation; GLMMa — GLMMadaptive ; TMB — glmmTMB ; SAS — PROC NLMIXED ; STATA — menbreg .

    Article Snippet: In the remainder of the paper, we will refer to the use of menbreg command with the AGHQ as “STATA.”

    Techniques: Software

    Estimated standard errors of the estimates of the mean-structure coefficients of the two-level model for the different software implementations and the 9112 genes, for which the two-level model was successfully fitted for all the implementations. The densities of the estimated standard errors are shown along the diagonal. The lower triangle contains Bland–Altman plots of the estimates for pairs of different software implementations, with the red dashed line indicating the mean difference and the black dashed lines marking the 95% limits of agreement. The upper triangle presents the numerical values of the limits. Panel A: β 1 ; panel B: β 2 ; panel C: β 3 . LME4L — lme4 with the Laplace approximation; LME4A — lme4 with the AGHQ approximation; GLMMa — GLMMadaptive ; TMB — glmmTMB ; SAS — PROC NLMIXED ; STATA — menbreg .

    Journal: Bioinformatics Advances

    Article Title: A hierarchical negative-binomial model for analysis of correlated sequencing data: practical implementations

    doi: 10.1093/bioadv/vbaf126

    Figure Lengend Snippet: Estimated standard errors of the estimates of the mean-structure coefficients of the two-level model for the different software implementations and the 9112 genes, for which the two-level model was successfully fitted for all the implementations. The densities of the estimated standard errors are shown along the diagonal. The lower triangle contains Bland–Altman plots of the estimates for pairs of different software implementations, with the red dashed line indicating the mean difference and the black dashed lines marking the 95% limits of agreement. The upper triangle presents the numerical values of the limits. Panel A: β 1 ; panel B: β 2 ; panel C: β 3 . LME4L — lme4 with the Laplace approximation; LME4A — lme4 with the AGHQ approximation; GLMMa — GLMMadaptive ; TMB — glmmTMB ; SAS — PROC NLMIXED ; STATA — menbreg .

    Article Snippet: In the remainder of the paper, we will refer to the use of menbreg command with the AGHQ as “STATA.”

    Techniques: Software

    Estimates of ϕ and σ for the two-level model for the different software implementations and the 9112 genes, for which the model was successfully fitted for all the implementations. The densities of the estimates are shown along the diagonal. The lower triangle contains Bland–Altman plots of the estimates for pairs of different software implementations, with the red dashed line indicating the mean difference and the black dashed lines marking the 95% limits of agreement. The upper triangle presents the numerical values of the 95% limits of agreement. Panel A: ϕ ; panel B: σ . LME4L — lme4 with the Laplace approximation; LME4A — lme4 with the AGHQ approximation; GLMMa — GLMMadaptive ; TMB — glmmTMB ; SAS — PROC NLMIXED ; STATA — menbreg .

    Journal: Bioinformatics Advances

    Article Title: A hierarchical negative-binomial model for analysis of correlated sequencing data: practical implementations

    doi: 10.1093/bioadv/vbaf126

    Figure Lengend Snippet: Estimates of ϕ and σ for the two-level model for the different software implementations and the 9112 genes, for which the model was successfully fitted for all the implementations. The densities of the estimates are shown along the diagonal. The lower triangle contains Bland–Altman plots of the estimates for pairs of different software implementations, with the red dashed line indicating the mean difference and the black dashed lines marking the 95% limits of agreement. The upper triangle presents the numerical values of the 95% limits of agreement. Panel A: ϕ ; panel B: σ . LME4L — lme4 with the Laplace approximation; LME4A — lme4 with the AGHQ approximation; GLMMa — GLMMadaptive ; TMB — glmmTMB ; SAS — PROC NLMIXED ; STATA — menbreg .

    Article Snippet: In the remainder of the paper, we will refer to the use of menbreg command with the AGHQ as “STATA.”

    Techniques: Software