Sentences with phrase «estimating equations models»

We reran the main generalized estimating equations model for a subsample of women who underwent screening for gestational diabetes mellitus at Mount Sinai Hospital.

Internalising and externalising behaviour was related to father involvement in crude and adjusted logistic regression and generalised estimating equation models.

Not exact matches

We built a generalized estimating equation (GEE) general linear model (GLM) with outcome as the dependent variable; time in the nursing box, licking / grooming per puppy, vertical nursing per puppy, and ventral nursing per puppy were entered as predictors with breed, maternal parity, sex of puppy, and age at return entered as covariates.

In contrast with ACR's 2010 methodology for N2O Emissions Reductions from Changes in Fertilizer Management, which incorporates site specific data into a peer - reviewed, tested and highly parameterized computer model to calculate N2O emission reductions resulting from changes in how fertilizer is applied and used, the MSU - EPRI methodology is based on empirical equations and NCR data to set conservative estimates for emission reductions.

For a climate model that has some correlation with the past data the model estimates should be converted into a recalibrated estimate using the regression equation.

All three scenarios are assessed using MDM - E3, a macro-econometric model that applies economic (national) accounting identities and empirically estimated equations to model interactions between the UK economy, energy system and the environment.

Climate models are amalgams of fundamental physics, approximations to well - known equations, and empirical estimates (known as parameterizations) of processes that either can't be resolved (because they happen on too small a physical scale) or that are only poorly constrained from data.

Changes in rates of child diagnoses from baseline to 3 months as a function of mother's remission and subsequently mother's level of response were analyzed using a repeated measures analysis with binary response data, using generalized estimating equation (GEE) methods.27 A linear probability model with an identity link function (rather than a logit - link function) was used to model interactions on the additive scale28 and to model a dose - response function using rates (rather than odds) as the outcome measure because we considered risk differences to be a more relevant measure than odds ratios in our study.

The results of mediation analysis using structural equation modeling showed that maternal problems in reciprocal social behavior directly increased infantile aggression (estimate = 0.100, 95 % CI [0.011, 0.186]-RRB-, and indirectly increased infantile aggression via maternal postpartum depressive symptoms (estimate = 0.027, 95 % CI [0.010, 0.054]-RRB-, even after controlling for covariates.

For all models, logistic regression was undertaken within the generalised estimating equations framework to account for the correlations within a family.

Individually significant coefficients were interpreted only if the equation in which they were estimated was significant as a whole in a multivariate test, an approach that minimizes the problem of false positives due to multiple comparisons while avoiding the problem of low power to detect true associations of moderate magnitude that is introduced by more conservative methods (eg, Bonferroni corrections).33 Model comparisons were made using the Akaike information criterion.34

This model was fitted by using population - averaged Generalized Estimating Equation methods.

Risk factors associated with these rates were analyzed using generalized estimating equations with a Poisson model.

To do this, we repeated the previous analyses except we also entered the dummy code indicating whether wives were using HCs at relationship formation to account for variance in the intercept and current HC status slope estimates in the second level of the model to create the current HC status × HC status at relationship formation interaction with the following equation (Eq.

Marginal logistic regression models were fitted for repeated - measures data (eg, well - child visits) using generalized estimating equations with working - independence covariance structures.28

The data was analyzed using generalized linear models and generalized estimating equations, which are specifically used to address the multilevel design of data in which schools with participating schoolchildren were randomized (rather than individual participants).

Multiple - group models estimated in structural equation modeling suggested that youth who were higher in social anxiety or coping efficacy problems were more likely to transmit emotional reactivity developed in the family - of - origin to emotional reactivity in response to conflict in close friendships.

Method: We used a new ACE structural equation model to estimate heritability from a case - control family study of BED conducted in the Boston area.

Such an approach is ideal for examining mediation models that include repeated measures, and given that the model is estimated in a single equation, one can directly estimate the covariance of the random effects that are encompassed in different Level 1 and Level 2 models.

Hypotheses were tested using structural equation modeling with a latent variable interaction estimated in Mplus version 7.3 (Muthén and Muthén 1998 — 2012).

Fifth, we estimated the path model presented in Figure 1 using structural equation modeling.

Because of skewness and the ordered categorical nature of our variables, we estimated α within a structural equation model framework, which resulted in higher α coefficients.20 Our ω reliability analyses yielded results consistent with previous studies reporting ω reliabilities for preschool and school - age SDQs.9, 16

A cumulative logit function was used to estimate the model parameters via the generalized estimating equations.31 The dependence of responses within clusters was specified using an exchangable working correlation structure.

Generalized estimating equations (GEE) models showed small, but significant positive treatment effects on parental self - efficacy, and marginally significant effects on social support, and knowledge on child rearing.

A series of generalized estimating equation (GEE) models were used to examine proposed relations.

Our data were analyzed using the Generalized Estimating Equations (GEE) approach because this extension of the General Linear Model can empirically account for both positive and negative correlations of the observations within couples.

We aim to estimate the pathways between maternal symptoms of anxiety and depression and child nocturnal awakenings via structural equation modeling using a sibling design.

Robust inference using weighted - least squares and quadratic estimating equations in latent variable modeling with categorical and continuous outcomes