Methodological Study On Meta-Analysis Of Ordinal Data

BackgroundIn recent years,evidence based medicine(EBM)has grown rapidly.Evidence-based medical research based on meta-analysis also serves as a high-level evidence to guide clinical practice.At present,the meta-analysis methods for the mean,rate,and survival outcome data has been fully applied and developed,and its methodology is also relatively mature.However,there is currently no good meta-analysis method for the analysis of ordinal data.For ordinal outcome data,meta-analysis methods are currently used to approximate the ordinal data as continuous data or split it into dichotomous outcomes and then use the meta-analysis methods of mean or rate data for analysis.This operation will undoubtedly lose data information and may even lead to erroneous conclusions.In view of this,this study intends to conduct a meta-analysis of ordinal data.Alan Agresti proposed the Generalized Odds Ratios(GenOR)values between the two groups for ordinal data in 1980.When there are only two types of grades,it is exactly the OR value for the proportion data comparisons,so it can be treated as a generalization of the OR for the proportion data.The GenOR provides a good basis for the study of the meta-analysis of ordinal data because of the good statistical properties.ObjectiveThis study intends to construct a meta-analysis method based on the OR of ordinal data-GenOR for the comparison of two sets of ordinal data sets under parallel design and paired design,and to construct a fixed-effects model and a random-effects model simultaneously to meet the needs of different applications.MethodThe study first calculates the GenOR statistics for each study and then weights them based on the inverse variance weighting method,the combined effects were obtained under the fixed effect model and the random effect model respectively,and their 95%confidence intervals were constructed.All methods use Monte Carlo statistical simulations to evaluate their statistical performance.The evaluation indicators include 95%confidence interval coverage,one-sided non-coverage ratio,point estimation bias,mean difference percentage,and mean square error(MSE).ResultIn this study,a meta-analysis of parallel design and matching design was constructed based on inverse variance weighting method,including fixed effects model and random effects model.For the parallel design,the simulation study shows that in the case of large samples and small samples,the point estimation error,the percentage difference in average,the mean square error are small,and the 95%confidence interval coverage is close to 95%,indicating that point estimates and interval estimates are quite accurate.For the paired design,the simulation study shows that,the point estimation error,the percentage difference in average,the mean square error are small,and the 95%confidence interval coverage is close to 95%,showing this method is also suitable for matching design data.ConclusionThe meta-analysis method of ordinal data constructed in this study has excellent statistical performance except the random effect model under parallel design and can meet application requirements,and it is recommended for application.