GainIndex | R Documentation |
This function computes the Gain Index and other related statistics for educational trials. Gain index provides a proportion of pupils who would not have make good progress without intervention. This function supports flexible configurations for JAGS modeling.
GainIndex(
data,
formula,
random,
intervention,
NA.omit = TRUE,
n.iter = 20000,
n.chains = 3,
n.burnin = 10000,
inits = NULL,
model.file = NULL,
alpha = 0.05
)
data |
A list containing the data for the JAGS model which must include columns: School, Posttest, Pretest, Intervention. Data should not have any missing values in these columns. |
formula |
the model to be analysed is of the form y ~ x1+x2+.... Where y is the outcome variable and Xs are the independent variables. Formula does not need to include |
random |
a string variable specifying the "clustering variable" as contained in the data. See example below. |
intervention |
a string variable specifying the "intervention variable" as appearing in the formula and the data. See example below. |
NA.omit |
Optional; a logic to check if omitting missing value. If NA.omit = TRUE, results will output the percentage of missing value in the four required columns and then JAGS results. If NA.omit = FALSE, will give a warning "Please handle missing values before using GainIndex()." If not provided, the function uses default TRUE. |
n.iter |
Total number of iterations for the MCMC simulation. |
n.chains |
Number of chains to run in the MCMC simulation. |
n.burnin |
Number of burn-in iterations to be discarded before analysis. |
inits |
Optional; a list of initial values for the JAGS model. If NULL, the function generates default initial values. |
model.file |
Optional; a custom path to the JAGS model file. If not provided, the function uses default path. |
alpha |
significant level, default alpha = 0.05. |
An S3 object containing the following components:
A data frame containing the Gain Index and its 95% confidence intervals, as well as the Progress Index and its 95% confidence intervals.
A data frame showing the proportion of participants achieving each level of gain (low and high) for both control and intervention groups.
A vector with execution time details, including user and elapsed time in seconds.
######### EXAMPLE ONE: crtData #########
## Not run:
data(crtData)
output1 <- GainIndex(data = crtData, formula = Posttest~Prettest, random = "School",n.iter = 200,
intervention = "Intervention", NA.omit = T, alpha = 0.05)
output1
########## EXAMPLE TWO: mstData ######
data(mstData)
output1 <- GainIndex(data = mstData, formula = Posttest~Prettest, random = "School",n.iter = 200,
intervention = "Intervention", NA.omit = T, alpha = 0.05)
output1
## End(Not run)
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