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Table 2 Characteristics of the determinants of (and) the statistical methods used for analysing the primary outcomes in cluster trials

From: Statistical analysis of publicly funded cluster randomised controlled trials: a review of the National Institute for Health Research Journals Library

Characteristics

n

%

Type of follow-up RCT (N = 86)

Closed cohort follow-up

76

88

Open cohort follow-up

4

5

Cross-sectional

4

5

Repeated cross-sectional

2

2

Data type of primary outcome (N = 100)

Continuous

63

63

Binary

28

28

Counts

5

5

Time to event

2

2

Percentage

2

2

Method of adjusting for clustering (N = 100)

Cluster-level analysis:

  

 Standard generalized linear model

2

2

Individual-level analysis:

  

 Generalized linear mixed model

80

80

 Robust standard errors

7

7

 Generalized estimating equations

6

6

Clustering not accounted for:

  

 Statistical hypothesis test statistic—chi-square

1

1

  Standard generalized linear model

4

4

Specific statistical model (N = 100)

Linear regression

57

57

Logistic regression

25

25

Analysis of covariance

6

6

Relative sensitivity

1

1

Negative binomial regression

2

2

Analysis of proportions

1

1

Cox Proportional Hazards model

2

2

Poisson regression

4

4

Weibull regression model

1

1

Chi-square test

1

1

Random component of GLMM (N = 80)

Random intercept

76

95

Shared frailty

1

1

Random intercept and slope (repeated measures)

3

4

Correlation structure in GEE (N = 6)

Exchangeable correlation

5

83

Correlation structure not reported

1

17

  1. N = total number of trials; n = counts observed in each level of a category; RCT = randomised controlled trial; GLMM = generalized linear mixed model; GEE = generalized estimating equations. Not reported means that the information of interest was not considered and/or provided in the trial