Sentences with phrase «logistic regression analysis model»

«Machine learning offers new way of designing chiral crystals: Logistic regression analysis model predicts ideal chiral crystal.»

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).

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

Kaplan - Meier and Cox proportional hazards survival analyses were used in unadjusted and adjusted analyses of the effect of pacifier use on breastfeeding duration.19 Logistic regression modeling was used to evaluate the effect of pacifier timing on breastfeeding duration.20 Significance levels were not adjusted for multiple comparisons.

We modeled the association between early breastfeeding experiences and postpartum depression as a complete case analysis using logistic regression in SAS 9.1.

In the analysis, we considered multiple covariates that may confound the association between early breastfeeding experience and postpartum depression based on the published literature and included these covariates in our multivariable logistic regression models.

After examining the unadjusted, bivariate associations with delayed OL, we used logistic regression analysis to estimate the adjusted odds ratio (OR) and 95 % CI in multiple variable models.

Burton and Dickey then developed logistic regression and random forest models using the ArmChair Analysis play - by - play data seasons to predict future play types.

As described in the main text, ordered logistic regression analyses were carried out for each brain region in which social network distances were modeled as a function of local neural response similarities and dyadic dissimilarities in control variables (gender, ethnicity, nationality, age, and handedness).

In February of 2011, CUNY's Office of Institutional Research and Assessment, headed by University Dean David Crook, released critical data (obtained by Director of Policy Analysis Colin Chellman using linear probability models and logistic regression) demonstrating that, all else being equal (i.e., taking into account all measurable demographic and performance characteristics), CUNY's transfer students were at a disadvantage in terms of graduation compared to native students.

Specific statistical areas of expertise include factor and cluster analysis, basic bivariate analyses, repeated measures analyses, linear and hierarchical / mixed models, structural equation modeling, and nonparametric analyses including logistic regression techniques.

I also taught myself a fair bit of statistics along the way including logistic regressions and discriminant analysis in order to backtest different models for identifying outperformers, dividend growth / cuts etc..

Performed advanced statistical analysis (univariate and multivariate analysis of variance, cluster and path analysis, principle component and factor analysis, analysis of covariance, survival & longitudinal analysis, logistic and linear regression modeling), created customized reports and presentation quality data summary tables and figures.

Using logistic regression analysis, odds ratios, 95 % confidence intervals and significance p values were estimated for association between each outcome and each childhood measure individually and in models including all childhood measures, each adjusted for cohort and gender.

Topics Include Exploratory Data Analysis, Multiple Regression, Logistic Regression, Correlation, Multivariate Analysis Of Variance (manova), Factorial Analysis Of Variance (anova), Factor Analysis And Principal Components, Discriminant Analysis, Structural Equation Modeling, And Emerging Data Analysis Techniques.

Multiple mediation analyses utilising linear and logistic regression models as appropriate were used to further investigate the extent to which the association between sports club membership and each of the three SES indicators was mediated by the three potential mediators.

She has technical expertise in a wide range of statistical techniques used in the social sciences, including structural equation modeling, confirmatory factor analysis and MIMIC approaches to measurement, path modeling, regression analysis (e.g., linear, logistic, Poisson), latent class analysis, hierarchical linear models (including growth curve modeling), latent transition analysis, mixture modeling, item response theory, as well as more commonly used techniques drawing from classical test theory (e.g., reliability analysis through Cronbach's alpha, exploratory factor analysis, uni - and multivariate regression, correlation, ANOVA, etc).

The statistical analysis is based on logistic regression models and is used to determine whether the duration of poverty is associated with the indicators of child well - being used above.

Couple - level multivariate logistic regression models, weighted to account for the complex sampling design, were used in the analysis.

Additional exploratory analyses including correlation coefficients and further ANCOVA and logistic regression models may be used to identify the characteristics of subsets of participants who respond particularly well or poorly to the addition of HPS to IYP.

Separately for boys and girls, we fitted logistic regression models for risk of behaviour problems assessed by each SDQ scale (total difficulties and prosocial) in each analysis period [30].

In the second part of the analyses, multinomial logistic regression models were used to examine which variables2 would discriminate between trajectories of social anxiety (Duchesne et al. 2010).