Sentence examples for both conditional logistic regression from inspiring English sources
For both conditional logistic regression and the exploratory polytomous regression, we assessed whether other variables were potential confounders, such as age, education, smoking history, alcohol consumption, body mass index, age at menarche, and parity.
In both phases, conditional logistic regression is used to fit statistical models to the different cis-eQTL data sets.
Both analyses used conditional logistic regression, matching on stratum.
Both unconditional and conditional logistic regression analyses were used to estimate the odds ratio (OR) and 95% confidence interval (CI) in regard to relevant exposure variables.
It showed independent effects through both stepwise and conditional logistic regression, and there is no evidence of other independent association signals for SLE in this region.
Bivariate analyses to test for independent associations between potentially confounding variables and both case status (conditional logistic regression) and circulating 25(OH D concentrations among controls (linear regression) based on the Wald test were conducted.
In order to highlight the importance of independent factors that influence the issue of unwanted pregnancies, both unconditional and conditional logistic regression analysis in the form of case control design has been performed.
We used both a forward and backward stepwise (conditional) logistic regression model with SPSS 12.0.1 for analyzing relationships with haplogroup frequencies.
We tested the hypothesis of selective effects of rainfall on the Y chromosome in both a forward and backward stepwise (conditional) logistic regression.
To estimate the risk of HGD and OAC among patients with BO, matched and adjusted ORs (ORa) with 95% CIs were calculated using conditional logistic regression for both databases separately and as a pooled analysis on patient-level pooled data.
The associations of dietary patterns and quality scores with BC risk were evaluated using separate conditional logistic regression models, both in quartiles and as a continuous term (per s.d. increment).
