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Seven papers used non-parametric methods, three papers used parametric methods, one paper used negative binomial regression, one paper stated that the Cochran-Mantel-Haenszel test was used, and one paper used either the two-sample T test or the Wilcoxon-Mann-Whitney test.
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This supported conducting parallel and separate negative binomial regression analysis on the two crime types.
These three separate outcomes will be analyzed together by multinomial logistic regression rather than by separate binomial logistic regressions (one for each outcome).
This variable was modelled using zero-truncated negative binomial regression, since its minimum value is one and it is over-dispersed.
Then, among children who spent at least one day underimmunized, negative binomial regression was used to evaluate the impact of PCV introduction on the discrete outcome, number of days spent underimmunized by 13 months.
One time-trend analysis presented hazard ratios based on negative binomial regression and was not adjusted for age, sex, stage of participants [ 30].
One weakness with the binomial regression model used is that some covariate combinations may give negative smoking prevalence.
The primary analyses will compare between intervention and control periods (1) the rate of falls (falls per 1000 patient days) using negative binomial regression, (2) the proportion of patients who experience one or more falls versus no falls using logistic regression and (3) the rate of falls resulting in injury using negative binomial regression.
Relative risk of being downloaded or cited one time are modeled with a multiple negative binomial regression.
Repeated falls in the past year were more highly predictive of falls during the following year – IRR 4.7, 95% CI 2.6 8.7 – than just one – IRR 3.6, 95% CI 2.0 6.3, using negative binomial regression.
Study-specific log binomial regression models were also fitted with PROC GENMOD in SAS, version 9. One-stage meta-analyses were fitted with SAS, version 9, PROC GLIMMIX.
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