Sentences with phrase «binary logistic»

Analyses were conducted using linear regression for continuous outcomes and binary logistic regression for categorical outcomes.

Coefficients from binary logistic regression models predicting «abnormal» emotional outcomes at preschool

Binary logistic regression was employed for multivariable analysis, as the dependent variable was dichotomous.

Multiple - parameter analyses were performed using binary logistic analysis, calculating ORs and 95 % CIs to adjust confounding factors.

Binary logistic regression with the enter method was used to find out the significant variables at level of 0.05 % and the CI of odds ratio (OR) was calculated.

Similar to the ACE Study analyses, for each outcome variable, a binary logistic regression was applied to test the relationship of the adversity index score (0, 1, 2, 3, or ≥ 4) to the outcome, after entering the control variables (child's sex, child's race / ethnicity, caregiver's marital status, and family income).

The participants were categorized as CI or BRI and referents, and binary logistic regression analysis was applied.

It is an observational study involving secondary analysis of maternity records, using binary logistic regression modelling.

Not exact matches

The analysis was carried out using a logistic binary regression model, with PPH as the outcome variable and built using manual forward selection (with p < 0.05 as the cut - off).

Statistical significance tests were based upon logistic regression20 and a series of binary explanatory covariates.

All three systems — multinomial logit regression, dynamic signal extraction and the University's refined binary logit model — use the technique of logistic regression to analyse various indicators, such as a country's exposure to debt, foreign trade, domestic growth and government expenditure.

Models were specified either as ordered logistic regressions with categorical social distance as the dependent variable or as logistic regression with a binary indicator of reciprocated friendship as the dependent variable.

Using logistic regression and Cox proportional hazards models, we identified genetic variants associated with binary and time - to - event PSC subphenotypes.

Presence of FMc was treated as a binary outcome in logistic regression models, with age at diagnosis and various disease characteristics as the predictors.

To investigate the relationship between learning styles, teacher demographics, and teacher retention, bivariate logistic regression analyses were conducted, and interactions between variables were tested for their predictive relationship with the binary outcome (retention).

To probe these findings further, we conducted a set of logistic regression analyses using teacher retention through Year 2 as our binary outcome.

Several analyses focused on missing data.36 To explore missing data patterns, we coded loss to follow - up as a binary variable and tested baseline variables as predictors using a stepwise logistic regression.

Logistic generalised estimating equations (GEEs) were used to investigate the associations between the adolescent drinking variables and the repeated binary measures of AUDs in adulthood.

The Sweep 4 Maternal Mental Health Report uses logistic regression - a method that summarises the relationship between a binary «dependent» variable (one that takes the values» 0» or» 1») and one or more «independent» explanatory variables.

The ecological analyses employed logistic regression because sexual risk behavior was operationalized as a binary outcome.

General Linear Models (GLM, for psychological quantitative measures) and logistic regressions (for binary measures) assessed the specific contribution of CU levels and the presence of ODD diagnosis on the psychological measures.

Primary and secondary outcomes will be analyzed using multiple regression for continuous outcomes, and logistic regression for binary outcomes controlling for baseline scores where possible.