Bmc Med Res Methodol
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Bmc Med Res Methodol · Jan 2013
Comparative StudyComparison of population-averaged and cluster-specific models for the analysis of cluster randomized trials with missing binary outcomes: a simulation study.
The objective of this simulation study is to compare the accuracy and efficiency of population-averaged (i.e. generalized estimating equations (GEE)) and cluster-specific (i.e. random-effects logistic regression (RELR)) models for analyzing data from cluster randomized trials (CRTs) with missing binary responses. ⋯ GEE performs well as long as appropriate missing data strategies are adopted based on the design of CRTs and the percentage of missing data. In contrast, RELR does not perform well when either standard or within-cluster MI strategy is applied prior to the analysis.
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Bmc Med Res Methodol · Jan 2013
Statistical process control of mortality series in the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database: implications of the data generating process.
Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. ⋯ The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. False-positive signalling of the raw mortality series was evident with respect to RA-EWMA control limits. A time series approach using residual control charts resolved these issues.
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Bmc Med Res Methodol · Oct 2012
Randomized Controlled TrialAn exploration of the missing data mechanism in an Internet based smoking cessation trial.
Missing outcome data are very common in smoking cessation trials. It is often assumed that all such missing data are from participants who have been unsuccessful in giving up smoking ("missing=smoking"). Here we use data from a recent Internet based smoking cessation trial in order to investigate which of a set of a priori chosen baseline variables are predictive of missingness, and the evidence for and against the "missing=smoking" assumption. ⋯ Those conducting smoking cessation trials, and wishing to perform an analysis that assumes the data are MAR, should collect and incorporate baseline variables into their models that are thought to be good predictors of missing data in order to make this assumption more plausible. However they should also consider the possibility of Missing Not at Random (MNAR) models that make or allow for less extreme assumptions than "missing=smoking".
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Bmc Med Res Methodol · Sep 2012
Adjustment for reporting bias in network meta-analysis of antidepressant trials.
Network meta-analysis (NMA), a generalization of conventional MA, allows for assessing the relative effectiveness of multiple interventions. Reporting bias is a major threat to the validity of MA and NMA. Numerous methods are available to assess the robustness of MA results to reporting bias. We aimed to extend such methods to NMA. ⋯ In this case study, adjustment models showed that NMA of published data was not robust to reporting bias and provided estimates closer to that of NMA of FDA data, although not optimal. The validity of such methods depends on the number of trials in the network and the assumption that conventional MAs in the network share a common mean bias mechanism.
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Bmc Med Res Methodol · Sep 2012
Reliability, validity and administrative burden of the community reintegration of injured service members computer adaptive test (CRIS-CAT)".
The Computer Adaptive Test version of the Community Reintegration of Injured Service Members measure (CRIS-CAT) consists of three scales measuring Extent of, Perceived Limitations in, and Satisfaction with community integration. The CRIS-CAT was developed using item response theory methods. The purposes of this study were to assess the reliability, concurrent, known group and predictive validity and respondent burden of the CRIS-CAT.The CRIS-CAT was developed using item response theory methods. The purposes of this study were to assess the reliability, concurrent, known group and predictive validity and respondent burden of the CRIS-CAT. ⋯ The CRIS-CAT demonstrated sound measurement properties including reliability, construct, known group and predictive validity, and it was administered with minimal respondent burden. These findings support the use of this measure in assessing community reintegration.