Sentence examples for binary and continuous outcomes from inspiring English sources

We compared the distribution of heterogeneity in meta-analyses of binary and continuous outcomes.

To provide GRADE guidance for assessing risk of bias across an entire body of evidence consequent on missing data for systematic reviews of both binary and continuous outcomes.

Binary and continuous outcomes were analyzed separately.

The statistical models (for both binary and continuous outcomes) were built as follows.

Different effect measures can be used for both binary and continuous outcomes (see item 13).

Statistical analysis: Unadjusted ORs and mean differences were calculated for binary and continuous outcomes, respectively.

We estimated disease odds using GAMs, a form of nonparametric or semiparametric regression with the ability to analyze binary and continuous outcome data while adjusting for covariates (Hastie and Tibshirani 1990; Kelsall and Diggle 1998; Webster et al. 2006).

We estimated local disease odds using generalized additive models, a form of non-parametric or semi-parametric regression with the ability to analyze binary and continuous outcome data while adjusting for covariates [ 13, 18].

In the remainder of this section the mathematical models for binary and continuous outcome measures are described beginning with simple meta-analytic models which are then extended to MTC models including baseline characteristics and other assumptions necessary for the RA model.

Small-study effect has been observed when examining meta-analysis with binary [ 3] and continuous outcomes [ 4].

Primary inferential analyses consisted of random coefficient multilevel (i.e., HLM) models that contained random intercepts or random intercepts and slopes to model within-participant correlations of responses over time, providing a unified method to model both binary (i.e., nonadherence) and continuous outcomes (i.e., the coping measures).