зеркало из https://github.com/microsoft/wpa.git
111 строки
3.6 KiB
R
111 строки
3.6 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/create_ITSA.R
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\name{create_ITSA}
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\alias{create_ITSA}
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\title{Estimate an effect of intervention on every Viva Insights metric in input
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file by applying single-group Interrupted Time-Series Analysis (ITSA)}
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\usage{
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create_ITSA(
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data,
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before_start = min(as.Date(data$Date, "\%m/\%d/\%Y")),
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before_end,
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after_start,
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after_end = max(as.Date(data$Date, "\%m/\%d/\%Y")),
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ac_lags_max = 7,
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return = "table"
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)
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}
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\arguments{
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\item{data}{Person Query as a dataframe including date column named \code{Date}.
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This function assumes the data format is MM/DD/YYYY as is standard in a
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Viva Insights query output.}
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\item{before_start}{Start date of 'before' time period in MM/DD/YYYY format
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as character type. Before time period is the period before the intervention
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(e.g. training program, re-org, shift to remote work) occurs and bounded by
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before_start and before_end parameters. Longer period increases likelihood
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of achieving more statistically significant results. Defaults to earliest
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date in dataset.}
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\item{before_end}{End date of 'before' time period in MM/DD/YYYY format as
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character type.}
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\item{after_start}{Start date of 'after' time period in MM/DD/YYYY format as
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character type. After time period is the period after the intervention
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occurs and bounded by after_start and after_end parameters. Longer period
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increases likelihood of achieving more statistically significant results.
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Defaults to date after before_end.}
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\item{after_end}{End date of 'after' time period in MM/DD/YYYY format as
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character type. Defaults to latest date in dataset.}
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\item{ac_lags_max}{maximum lag for autocorrelation test. Default is 7}
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\item{return}{String specifying what output to return. Defaults to "table".
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Valid return options include:
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\itemize{
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\item \code{'plot'}: return a list of plots.
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\item \code{'table'}: return data.frame with estimated models' coefficients and
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their corresponding p-values You should look for significant p-values in
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beta_2 to indicate an immediate treatment effect, and/or in beta_3 to
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indicate a treatment effect over time
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}}
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}
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\description{
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r lifecycle::badge('experimental')
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This function implements ITSA method described in the paper 'Conducting
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interrupted time-series analysis for single- and multiple-group comparisons',
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Ariel Linden, The Stata Journal (2015), 15, Number 2, pp. 480-500
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This function further requires the installation of 'sandwich', 'portes', and
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'lmtest' in order to work. These packages can be installed from CRAN using
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\code{install.packages()}.
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}
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\details{
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This function uses the additional package dependencies 'sandwich' and
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'lmtest'. Please install these separately from CRAN prior to running the
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function.
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As of May 2022, the 'portes' package was archived from CRAN. The dependency
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has since been removed and dependent functions \code{Ljungbox()} incorporated into
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the \strong{wpa} package.
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}
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\examples{
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# Returns summary table
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create_ITSA(
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data = sq_data,
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before_start = "11/03/2019",
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before_end = "12/15/2019",
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after_start = "12/29/2019",
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after_end = "1/26/2020",
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ac_lags_max = 7,
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return = "table")
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# Returns list of plots
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plot_list <-
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create_ITSA(
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data = sq_data,
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before_start = "11/03/2019",
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before_end = "12/15/2019",
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after_start = "12/29/2019",
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after_end = "1/26/2020",
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ac_lags_max = 7,
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return = 'plot')
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# Extract a plot as an example
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plot_list$Workweek_span
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}
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\seealso{
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Other Flexible Input:
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\code{\link{period_change}()}
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}
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\author{
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Aleksey Ashikhmin \href{mailto:alashi@microsoft.com}{alashi@microsoft.com}
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}
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\concept{Flexible Input}
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\concept{Interrupted Time-Series Analysis}
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