Sentence examples for multivariate stepwise forward from inspiring English sources

We performed multivariate, stepwise (forward) logistic regression.

Considering log ZnT8A or log IA-2βA as dependent variables, parameters that came out with P < 0.1 in univariate analysis were further tested in a multivariate stepwise forward linear regression model.

The effect of TIMP-3 differential expression on postoperative survival rates was assessed with both univariate (log-rank test) and multivariate (stepwise forward Cox's proportional-hazards regression model) analysis; p ≤ 0.05 was considered statistically significant.

Univariate and multivariate (stepwise, forward selection) regression analyses were performed to identify demographic (age, sex and home care/residential care) and neuropsychiatric subgroups (hyperactivity, psychotic symptoms, mood symptoms and apathy) associated with anti-dementia drug use.

The effect of EGFR and pEGFR differential expression on postoperative survival rates was assessed using both univariate (log-rank test) and multivariate (stepwise forward Cox's proportional hazard regression model) analysis.

Logistic multivariate stepwise regression (forward) was used to determine the influencing factors.

Determinants for high CT risk and CT testing were assessed using univariate and multivariate (using stepwise forward procedure) regression analyses.

The dependence of disease free survival (DFS), distant disease free survival (DDFS) and overall survival (OS) on the examined factors was calculated by Kaplan-Meier analysis (log-rank test, univariate), and cox regression analysis (multivariate, inclusion stepwise forward).

The independent effects of factors that were significantly associated with hypernatreamia were investigated in multivariate analysis using stepwise forward Wald logistic regression.

In study 1 (discovery analysis), following Motzer et al (1999, 2002) and Heng et al (2009), baseline factors were first individually evaluated for association with OS using a univariate Cox proportional hazards model, and subsequently evaluated using multivariate stepwise model selection (forward selection at P≤0.1 to enter the model and backward selection at P≤0.05 to stay in the model) (Table 2).

Multivariate logistic regression with stepwise forward entry.