Sentence examples for multivariable analysis were from inspiring English sources

Univariable and multivariable analysis were performed to investigate independent risk factors associated with arrest of descent during the second stage of labor and the perinatal outcome.

In order to identify predictors for death at 1 year of follow-up, a univariable analysis and a subsequent multivariable analysis were performed using a Cox proportional hazards regression model.

Other variables associated with clinical failure on multivariable analysis were history of vomiting, past history of use of bronchodilators, respiratory rate >10 breaths per minute above age specific cut off and non-adherence (Table 4).

Factors that were predictive of a smaller statin effect in a multivariable analysis were prospective study design, industry-independent funding, Asian study setting and a short follow-up time (in-hospital mortality).

Independent variables included in the multivariable analysis were chosen by means of backward selection with successive exclusion of the least significant variable until only significant predictors of study outcome remained in the model.

Among HIV-negative participants (Table 4), factors associated with a TB diagnosis in both univariable and multivariable analysis were a history of past TB treatment (adjusted hazard ratio (aHR): 2.18, 95% CI: 1.04 to 4.57), and older age (aHR: 2.07 [95% CI 0.88 4.89] for 35 45 years, 2.47 [95% CI: 1.22 to 5.02] for >45 years compared with <35 years).

A matched sampling technique with multivariable analysis was used to estimate cost.

Multivariable analysis was performed in order to quantify sensitivity and specificity for fracture prediction.

Multivariable analysis was performed to identify variables independently associated with ICDSC ≥4.

Pre-hospital variables associated with cTn-I elevation in multivariable analysis are reported in Table 8.

The results of the multivariable analysis are reported as mean difference with 95%% confidence intervals (CI).