Sentence examples for binary and continuous data from inspiring English sources

The current approach for evaluating the risk of random error in meta-analyses (MAs) using trial sequential analysis (TSA) can accommodate binary and continuous data but not time-to-event data.

Both binary and continuous data were reported in the selected papers.

However, both implement only basic methods for the meta-analysis of binary and continuous data (Table 1).

Published work on NMA mainly focuses on the synthesis of aggregate data (AD) (sometimes called summary data, e.g. group means and standard errors available from study reports) [ 4, 5]; however, methods have been developed that allow use of individual patient-level data (IPD) in NMA, specifically for binary and continuous data [ 6- 8].

Binary data and continuous data have been entered directly into RevMan as numbers of events or means and standard deviations, together with numbers of participants in each intervention group in each study.

The answers from these surveys were then converted into binary (0,1), ordinal, and continuous data for analysis.

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].

The CDSR includes four types of data which systematic review authors have extracted from the included studies: binary data, continuous data, generic results and "O-E and variance" data.

Generic results include time-to-event outcomes (e.g. analysed as hazard ratios) and ordinal outcomes (e.g. analysed as odds ratios), as well as binary or continuous data from studies with complex designs, while "O-E and variance" data are typically derived from time-to-event outcomes.

The clinical outcomes in our analysis can be categorized as binary or continuous data.