Create a Meta-Analysis Object Using Data From Previous Studies
Create a Meta-Analysis Object Using Data From Previous Studies
PosteriorATEDraws from the posterior distribution of the average treatment effect.
checksMCMC diagnostics
CredibleIntervalLower and upper bounds of the credible interval
PointEstimatePoint estimate of the average treatment effect
fittedStan fit object
new()Create a new meta analysis object.
metaAnalysis$new(
data,
point_estimates,
standard_errors,
id,
mean_mu = 0,
sd_mu = 0.05,
ci_width = 0.75,
X = NULL,
run_estimation = 1,
...
)dataData frame with data point estimates and standard errors from studies.
point_estimatesName of the variable in the data frame that contains the point estimates.
standard_errorsName of the variable in the data frame that contains the standard errors of the point estimates.
idName of the variable in the data frame that contains the id of the studies.
mean_muPrior mean for the true lift in the population.
sd_muPrior mean for the standard deviation of the true lift in the population.
ci_widthCredible interval's width.
XCovariates matrix.
run_estimationInteger flag to control whether estimation is run (1) or not (0).
...other arguments passed to rstan::sampling()
A new meta_analysis object.
PlotRawData()Plots the raw data.
metaAnalysis$PlotRawData()A plot with point estimates and 95% confidence intervals.
PlotLift()Plots lift's prior and posterior distributions.
For more details see vizdraws::vizdraws().
metaAnalysis$PlotLift(...)...other arguments passed to vizdraws.
An interactive plot of the prior and posterior distributions.
UpdateCI()Update the width of the credible interval.
metaAnalysis$UpdateCI(ci_width)ci_widthNew width for the credible interval. This number in the (0,1) interval.
probability()Calculates that probability that lift is between a and b.
metaAnalysis$probability(a = -Inf, b = Inf, percent = TRUE)aLower bound. By default -Inf.
bUpper bound. By default Inf.
percentA logical that indicates that a and b should be converted to percentage.
A string with the probability.
findings()Calculates the point estimate a credible interval for the meta analysis.
metaAnalysis$findings(percent = TRUE)percentA logical that indicates that the point estimate should be converted to percent.
A string with the findings
clone()The objects of this class are cloneable with this method.
metaAnalysis$clone(deep = FALSE)deepWhether to make a deep clone.
A meta analysis has raw data and draws from the lift's posterior distribution. This is represented by an R6 Class.