wp.mrt2arm: Statistical Power Analysis for Multisite Randomized Trials... In WebPower: Basic and Advanced Statistical Power Analysis

Description

Multisite randomized trials (MRT) are a type of multilevel design for the situation when the entire cluster is randomly assigned to either a treatment arm or a contral arm (Liu, 2013). The data from MRT can be analyzed in a two-level hierachical linear model, where the indicator variable for treatment assignment is included in first level. If a study contains multiple treatments, then mutiple indicators will be used. This function is for designs with 2 arms (i.e., a treatment and a control). Three types of tests are considered in the function: (1) The "main" type tests treatment main effect; (2) The "site" type tests the variance of cluster/site means; and (3) The "variance" type tests variance of treatment effects. Details leading to power calculation can be found in Raudenbush (1997) and Liu (2013).

Usage

 ```1 2 3``` ```wp.mrt2arm(n = NULL, f = NULL, J = NULL, tau00 = NULL, tau11 = NULL, sg2 = NULL, power = NULL, alpha = 0.05, alternative = c("two.sided", "one.sided"), type = c("main", "site", "variance")) ```

Arguments

 `n` Sample size. It is the number of individuals within each cluster. `f` Effect size. It specifies the main effect of treatment, the mean difference between the treatment clusters/sites and the control clusters/sites. Effect size must be positive. `J` Number of clusters / sites. It tells how many clusters are considered in the study design. At least two clusters are required. `tau00` Variance of cluster/site means. It is one of the residual variances in the second level. Its value must be positive. `tau11` Variance of treatment effects across sites. It is one of the residual variances in the second level. Its value must be positive. `sg2` Level-one error Variance. The residual variance in the first level. `power` Statistical power. `alpha` significance level chosed for the test. It equals 0.05 by default. `alternative` Type of the alternative hypothesis (`"two.sided"` or `"one.sided"`). The default is "two.sided". The option "one.sided" can be either "less" or "greater". `type` Type of effect (`"main"` or `"site"` or `"variance"`) with "main" as default. The type "main" tests treatment main effect, no tau00 needed; Type "site" tests the variance of cluster/site means, no tau11 or f needed; and Type "variance" tests variance of treatment effects, no tau00 or f needed.

Value

An object of the power analysis.

References

Liu, X. S. (2013). Statistical power analysis for the social and behavioral sciences: basic and advanced techniques. Routledge.

Raudenbush, S. W. (1997). Statistical analysis and optimal design for cluster randomized trials. Psychological Methods, 2(2), 173.

Zhang, Z., & Yuan, K.-H. (2018). Practical Statistical Power Analysis Using Webpower and R (Eds). Granger, IN: ISDSA Press.

Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66``` ```#To calculate the statistical power given sample size and effect size: #For main effect wp.mrt2arm(n = 45, f = 0.5, J = 20, tau11 = 0.5, sg2 = 1.25, alpha = 0.05, power = NULL) # Power analysis for Multileve model Multisite randomized trials with 2 arms # # J n f tau11 sg2 power alpha # 20 45 0.5 0.5 1.25 0.8583253 0.05 # # NOTE: n is the number of subjects per cluster # URL: http://psychstat.org/mrt2arm #For variance of treament effect wp.mrt2arm(n = 45, f = 0.5, J = 20, tau11 = 0.5, sg2 = 1.25, alpha = 0.05, power = NULL, type = "variance") # Power analysis for Multileve model Multisite randomized trials with 2 arms # # J n f tau11 sg2 power alpha # 20 45 0.5 0.5 1.25 0.9987823 0.05 # # NOTE: n is the number of subjects per cluster # URL: http://psychstat.org/mrt2arm #For testing site variablity res<- wp.mrt2arm(n = 45, f = 0.5, J = 20, tau11 = 0.5, sg2 = 1.25, alpha = 0.05, power = NULL, type = "site") # Power analysis for Multileve model Multisite randomized trials with 2 arms # # J n f tau11 sg2 alpha # 20 45 0.5 0.5 1.25 0.05 # # NOTE: n is the number of subjects per cluster # URL: http://psychstat.org/mrt2arm #To generate a power curve given a sequence of sample sizes: wp.mrt2arm(n = seq(10,50,5), f = 0.5, J = 20, tau11 = 0.5, sg2 = 1.25, alpha = 0.05, power = NULL) # Power analysis for Multileve model Multisite randomized trials with 2 arms # # J n f tau11 sg2 power alpha # 20 10 0.5 0.5 1.25 0.6599499 0.05 # 20 15 0.5 0.5 1.25 0.7383281 0.05 # 20 20 0.5 0.5 1.25 0.7818294 0.05 # 20 25 0.5 0.5 1.25 0.8090084 0.05 # 20 30 0.5 0.5 1.25 0.8274288 0.05 # 20 35 0.5 0.5 1.25 0.8406659 0.05 # 20 40 0.5 0.5 1.25 0.8506049 0.05 # 20 45 0.5 0.5 1.25 0.8583253 0.05 # 20 50 0.5 0.5 1.25 0.8644864 0.05 # # NOTE: n is the number of subjects per cluster # URL: http://psychstat.org/mrt2arm #To plot the power curve: plot(res) #To calculate the required sample size given power and effect size: wp.mrt2arm(n = NULL, f = 0.5, J = 20, tau11 = 0.5, sg2 = 1.25, alpha = 0.05, power = 0.8) # Power analysis for Multileve model Multisite randomized trials with 2 arms # # J n f tau11 sg2 power alpha # 20 23.10086 0.5 0.5 1.25 0.8 0.05 # # NOTE: n is the number of subjects per cluster # URL: http://psychstat.org/mrt2arm ```

WebPower documentation built on May 1, 2019, 8:19 p.m.