зеркало из https://github.com/microsoft/wpa.git
refactor: remove extra dependencies
'sandwich', 'lmtest', 'portes'
This commit is contained in:
Martin Chan
Родитель
3bf86107d7
Коммит
67f29a6614
11
DESCRIPTION
11
DESCRIPTION
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@ -12,6 +12,7 @@ Authors@R: c(
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person(given = "Lucas", family = "Hogner", role = "ctb", email = "lucas.hogner@microsoft.com"),
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person(given = "Jasminder", family = "Thind", role = "ctb", email = "jasminder.thind@microsoft.com"),
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person(given = "Simone", family = "Liebal", role = "ctb", email = "simone.liebal@microsoft.com"),
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person(given = "Aleksey", family = "Ashikhmin", role = "ctb", email = "alashi@microsoft.com"),
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person(given = "Ellen", family = "Trinklein", role = "ctb"),
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person(given = "Microsoft Corporation", role = "cph")
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)
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@ -54,10 +55,7 @@ Imports:
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proxy,
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ggwordcloud,
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methods,
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data.table,
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lmtest,
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portes,
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sandwich
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data.table
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RoxygenNote: 7.1.1
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Roxygen: list(markdown = TRUE)
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VignetteBuilder: knitr
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@ -67,5 +65,8 @@ Suggests:
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leiden,
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lifecycle,
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fst,
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glue
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glue,
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lmtest,
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portes,
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sandwich
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Language: en-US
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@ -6,7 +6,7 @@
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#' @title
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#' Estimate an effect of intervention on every WPA metric in input file by
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#' applying single-group Interrupted Time-Series Analysis (ITSA)
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#'
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#'
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#' @author Aleksey Ashikhmin <alashi@@microsoft.com>
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#'
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#' @description
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@ -16,25 +16,37 @@
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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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#'
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#' @param data Person Query as a dataframe including date column named 'Date'
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#' This function assumes the data format is MM/DD/YYYY as is standard in a WpA query output.
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#' @param before_start Start date of 'before' time period in MM/DD/YYYY format as character type.
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#' Before time period is the period before the intervention (e.g. training program, re-org, shift to remote work)
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#' occurs and bounded by before_start and before_end parameters. Longer period increases likelihood of achieving more statistically significant results.
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#' Defaults to earliest date in dataset.
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#' @param before_end End date of 'before' time period in MM/DD/YYYY format as character type.
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#' @param after_start Start date of 'after' time period in MM/DD/YYYY format as character type.
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#' After time period is the period after the intervention occurs and bounded by after_start and after_end parameters.
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#' Longer period increases likelihood of achieving more statistically significant results.
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#' Defaults to date after before_end.
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#' @param after_end End date of 'after' time period in MM/DD/YYYY format as character type. Defaults to latest date in dataset.
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#' @details
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#' This function uses the additional package dependencies 'sandwich', 'lmtest',
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#' and 'portes'. Please install these separately from CRAN prior to running the
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#' function.
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#'
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#' @param data Person Query as a dataframe including date column named `Date`.
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#' This function assumes the data format is MM/DD/YYYY as is standard in a WpA
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#' query output.
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#' @param 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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#' @param before_end End date of 'before' time period in MM/DD/YYYY format as
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#' character type.
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#' @param 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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#' @param 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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#' @param ac_lags_max maximum lag for autocorrelation test. Default is 7
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#' @param return String specifying what output to return. Defaults to "table".
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#' Valid return options include:
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#' - 'plot': return a list of plots.
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#' - 'table': return data.frame with estimated models' coefficients and their corresponding p-values
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#' You should look for significant p-values in beta_2 to indicate an immediate treatment effect,
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#' and/or in beta_3 to indicate a treatment effect over time
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#' - `'plot'`: return a list of plots.
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#' - `'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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#' @import dplyr
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#' @import ggplot2
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@ -47,7 +59,7 @@
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#'
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#'
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#' @examples
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#'
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#' \donttest{
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#' # Returns summary table
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#'
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#' create_ITSA(
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@ -73,7 +85,7 @@
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#'
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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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#' }
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#' @export
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create_ITSA <-
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@ -319,7 +331,7 @@ create_ITSA <-
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# the main title
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p_final <- p_final + theme(
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plot.title = element_text(color="blue", size=14, face="bold.italic"))
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# Save plot in list
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results_plot[[metric_name]] <- p_final
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}else{
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@ -16,35 +16,55 @@ create_ITSA(
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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 'Date'
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This function assumes the data format is MM/DD/YYYY as is standard in a WpA query output.}
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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 WpA
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query output.}
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\item{before_start}{Start date of 'before' time period in YYYY-MM-DD format as character type. Defaults to earliest date in dataset.}
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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 YYYY-MM-DD format as character type.}
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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 YYYY-MM-DD format as character type. Defaults to day after before_end.}
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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 YYYY-MM-DD format as character type. Defaults to latest date in dataset.}
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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 \code{"table"}.
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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 their corresponding p-values
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You should look for significant p-values in \code{beta_2} to indicate an immediate treatment effect,
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and/or in \code{beta_3} to indicate a treatment effect over time
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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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}
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\details{
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This function uses the additional package dependencies 'sandwich', 'lmtest',
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and 'portes'. Please install these separately from CRAN prior to running the
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function.
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}
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\examples{
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\donttest{
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# Returns summary table
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create_ITSA(
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@ -70,11 +90,14 @@ plot_list <-
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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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}
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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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