Sentences with phrase «by logistic regression analyses»

In investigating research question 2, indirect paths from the significant T1 predictors through T2 / T3 relationship satisfaction and child - rearing conflicts to late dissolutions were tested by logistic regression analyses using the SPSS Macro Process (Hayes [2013]-RRB-.

Individual weights were estimated by logistic regression analysis and trimming strategy.

Associations between the risk factors and relationship dissolution were estimated by logistic regression analysis.

Not exact matches

• In another Australian study, in multivariate logistic regression analyses «feeling close to the unborn baby» and a «high level of knowledge about the effects of passive smoking on baby» were associated with early quit attempts by fathers Moffatt & Stanton (2005).

Second, the associations between duration of breastfeeding and upper and lower respiratory and gastrointestinal tract infections in infants aged 6 and 12 months were analyzed by using multiple logistic regression analysis.

We examined independent associations by using multivariable logistic regression analysis.

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.

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.

Multiple logistic regression analysis was used to estimate the odds of pregnancy during the study by treatment arm (odds ratios [ORs] are presented with 95 % confidence intervals).

In addition, to assess whether there was an independent study effect on pregnancy rates by time period of recruitment into the study (before and after December 31, 2001), we included a time period variable in the multiple logistic regression analysis of the full study sample and found no effect.

Other risk factors were assessed and adjusted for by multivariable logistic regression analyses.

aChild Behavior Checklist for 4 - 18 years; bChildren who are currently visiting their father who used to perpetrate intimate partner violence and already separated from their mothers; cInternalizing problems = Withdrawn + Somatic complaints + Anxious / depressed; dExternalizing problems = Delinquent behavior + Aggressive behavior; Total problems = the sum of the scores of all the nine subscales of the CBCL; eAdjusted odds ratios calculated by multivariable logistic regression analysis; fThe dependent variable: 0 = non - clinical, 1 = clinical; gp values calculated by multivariable logistic regression analysis; hStandardized regression coefficients calculated by multivariable regression analysis; ip values calculated by multivariable regression analysis; jVariance Inflation Factor; k0 = non-visiting, 1 = visiting; lThe score of the subscale (anxiety) of the Hospital Anxiety and Depression Scale; mThe score of the subscale (depression) of the Hospital Anxiety and Depression Scale; nThe number of years the child lived with the father in the past; oAdjusted R2 calculated by multivariable regression analysis.

Associations between each of the baseline residential - environmental factors and five year survival were examined by multiple logistic regression analysis.

Logistic regression analyses were conducted to estimate the effect of maternal IPV on asthma diagnosed by age 36 months while adjusting for potential confounders (child's sex, age, race / ethnicity, low birth weight, maternal education, economic hardship, and tobacco exposure).

The study involved administering all 3 sets of scales to a general population sample who were then interviewed by clinical interviewers blinded to screening scales scores and classified as having or not having SMI based on 12 - month prevalences of DSM - IV disorders, as assessed by the Structured Clinical Interview (SCID) for DSM - IV16 and scores on the GAF.1 Logistic regression analyses were then carried out to estimate the strength of associations between the screening scales and SMI using linear and nonlinear prediction equations that assumed either additive or multiplicative associations among the different screening scales.

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.

Tables IV, V and VI show the results of the logistic regression analyses at T1, T2 and longitudinally predicting ever smoking by demographics (Step 1), anti-smoking parenting practices (Step 2), attitudes, social influences and self - efficacy (Step 3), and intention (Step 4), in order to shed light on the process by which parenting practices operate on smoking behavior and the role of smoking - specific cognitions and intention herein.

Logistic regression analyses were conducted to investigate the mediation hypotheses, using an established 3 - step procedure.48 First, we investigated whether there was a significant bivariate association between a high level of maladaptive parenting (operationally defined as ≥ 3 maladaptive parenting behaviors) or abuse during childhood or early adolescence (by a mean age of 14 years) and risk for suicide attempts during late adolescence or early adulthood (reported at a mean age of 22 years) and whether the magnitude of this association was reduced when interpersonal difficulties during middle adolescence (reported at a mean age of 16 years) were controlled statistically.

Research question 1 was investigated by multinomial logistic regression analyses with bootstrapping.

Multivariate logistic regression analyses examined parity progression by birth order, while multinomial logistic regression was used to identify associations between sex composition and use of permanent, temporary and traditional contraceptive methods.

Logistic Regression Analysis Predicting Lifetime Dignosis in Youth by Maternal Depression to Age 10 Years

A series of multi-level logistic and linear regression analyses were performed using the xtmelogit and xtmixed commands to test for mediation by cognitive factors.

The associations between the level of maternal relationship satisfaction and infectious disease in the group of < 6 - month - old infants were first tested by performing separate bivariate logistic regression analyses for each of the eight infectious diseases as the dependent variable, using the level of relationship satisfaction as the predictor variable.

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].