Binary outcome meta analysis odds ratio funnel and forest plot in R statistics
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- เผยแพร่เมื่อ 24 มิ.ย. 2023
- Subgroup, meta-analysis, binary, outcome, Risk ratio, effect size, estimate, statistical method, summary, pairwise group, results, multiple studies, clinical, research, medial, clinical trials, overall, pooled, intervention, treatment, exposure, control, reference, unexposed, event, probability, data, variability, heterogeneity, inconsistency, categorical, variable, binomial, dichotomous, levels, percentage, homogeneity, 95% confidence interval, p-value, weight percentage, descriptive statistics, diagram, publication bias, sample size, sample effort, single group, network, proportion, rate, frequency, continuous, percentage, standard deviation, standardized mean difference, prevalence, incidence, fixed effects, random effects, model, package, import, SPSS, STAT, Jamovi, R Statistics, Hedges’s, Cohen’s d, Glass’s delta, common effects, restricted maximum likelihood, RMLH, DerSimonia n-Laird, odds ratio, risk difference, correlation, mean difference, hazard ratio, peto’s odds ratio, Mantel-Haenszel, Inverse-Variance, no effect line, effect size line, egger’s regression, metprop, meta library, read, byvar, metabin, metacor, metacont, output, metagen, revaman, GraphPad Prism, metafor
This is the best I have seen on binary meta-analysis. Thank you so much!
Very clear and informative information
Excellent presentation and a wonderful youtube channel. This channel should have millions of subscribers.
Just one favor, Would you please create a playlist so we can navigate the videos easily?
Thanks in advance.
Hi, thank you so much for your video! I would like to ask a question regarding the pooling method you chose. You set the method as MH versus GLMM, Peto, or SSW. Can you please explain why? Thank you kindly.