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.
Not exact matches
We
examined independent associations by using multivariable
logistic regression analysis.
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.
To
examine the average association between, on the one hand, the categorical variables mentioned above, and on the other, being SGA, we simply calculated ORs and 95 % CIs obtained from
logistic regression analyses.
Associations between each of the baseline residential - environmental factors and five year survival were
examined by multiple
logistic regression analysis.
The effects of relationship dissatisfaction, life events, emotional distress, and demographic variables on the risk of relationship dissolution were
examined using
logistic regression analyses.
The relations between independent predictor variables (measures of immunological and psychological function at entry to the trial, age of onset, and duration of illness) and dependent dichotomous outcome variables (self rated global outcome; presence or absence of caseness on the general health questionnaire at follow up; reduced or normal delayed responses to hypersensitivity skin test) were
examined in separate
logistic regression analyses.
The co-occurrence of all combinations of the dichotomized child mental health problems (i.e., disruptive behavior, depression, somatization, ADHD, and anxiety) was
examined using conditional Odds Ratios obtained from a series of separate
logistic regression analyses.
Lifetime prevalences of antisocial syndromes were estimated and
logistic regression analyses were used to
examine associations between antisocial syndromes and sociodemographic characteristics and substance use disorders.
Logistic regressions were used to predict the likelihood of recovery at 18 months, and mixed - effects
regression analysis was applied to
examine the association of severity and rates of improvement across time in the two treatment groups.
Logistic regression analyses were conducted to
examine the research questions.
Second, we conducted multivariate
logistic regression analyses in which the association between attachment and mental health symptoms including depression, anxiety and posttraumatic stress symptoms was
examined, adjusting for age, gender, orphan status and adverse childhood experiences.
Multiple
logistic regression analysis was used to
examine perceived parental supervision and communication while controlling for relevant demographic and behavioral characteristics.
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).
Developmental patterns of six indices of peer relations (including group acceptance, group rejection, having a reciprocated best friend, social support from best friend, conflict with best friend, and the aggressiveness of the best friend) were
examined as predictors of aggression and delinquency using
logistic regression analyses.