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article Zou et al (2022) proposes a method for calculating probability of
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winning with a confidence interval an p-value testing.">< meta property = "og:description" content = "Calculates the probability of winning ( winP ) . In the referenced
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article Zou et al (2022) proposes a method for calculating probability of
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winning with a confidence interval an p-value testing.">< meta property = "og:image" content = "https://agdamsbo.github.io/stRoke/logo.png" > < / head > < body >
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< img src = "../logo.png" class = "logo" alt = "" > < h1 > Calculates the probability of winning< / h1 >
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< small class = "dont-index" > Source: < a href = "https://github.com/agdamsbo/stRoke/blob/v24.10.1/R/win_prob.R" class = "external-link" > < code > R/win_prob.R< / code > < / a > < / small >
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< div class = "d-none name" > < code > win_prob.Rd< / code > < / div >
< / div >
< div class = "ref-description section level2" >
< p > Calculates the probability of winning (winP). In the referenced
article Zou et al (2022) proposes a method for calculating probability of
winning with a confidence interval an p-value testing.< / p >
< / div >
< div class = "section level2" >
< h2 id = "ref-usage" > Usage< a class = "anchor" aria-label = "anchor" href = "#ref-usage" > < / a > < / h2 >
< div class = "sourceCode" > < pre class = "sourceCode r" > < code > < span > < span class = "fu" > win_prob< / span > < span class = "op" > (< / span > < / span >
< span > < span class = "va" > data< / span > ,< / span >
< span > response < span class = "op" > =< / span > < span class = "cn" > NULL< / span > ,< / span >
< span > group < span class = "op" > =< / span > < span class = "cn" > NULL< / span > ,< / span >
< span > alpha < span class = "op" > =< / span > < span class = "fl" > 0.05< / span > ,< / span >
< span > beta < span class = "op" > =< / span > < span class = "fl" > 0.2< / span > ,< / span >
< span > group.ratio < span class = "op" > =< / span > < span class = "fl" > 1< / span > ,< / span >
< span > sample.size < span class = "op" > =< / span > < span class = "cn" > FALSE< / span > ,< / span >
< span > print.tables < span class = "op" > =< / span > < span class = "cn" > FALSE< / span > ,< / span >
< span > dec < span class = "op" > =< / span > < span class = "fl" > 3< / span > < / span >
< span > < span class = "op" > )< / span > < / span > < / code > < / pre > < / div >
< / div >
< div class = "section level2" >
< h2 id = "source" > Source< a class = "anchor" aria-label = "anchor" href = "#source" > < / a > < / h2 >
< p > < a href = "https://doi.org/10.1161/STROKEAHA.121.037744" class = "external-link" > doi:10.1161/STROKEAHA.121.037744< / a > < / p >
< / div >
< div class = "section level2" >
< h2 id = "arguments" > Arguments< a class = "anchor" aria-label = "anchor" href = "#arguments" > < / a > < / h2 >
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< dl > < dt id = "arg-data" > data< a class = "anchor" aria-label = "anchor" href = "#arg-data" > < / a > < / dt >
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< dd > < p > A data frame containing the response and group variable.< / p > < / dd >
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< dt id = "arg-response" > response< a class = "anchor" aria-label = "anchor" href = "#arg-response" > < / a > < / dt >
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< dd > < p > The name of the response variable.
Takes first column if empty.< / p > < / dd >
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< dt id = "arg-group" > group< a class = "anchor" aria-label = "anchor" href = "#arg-group" > < / a > < / dt >
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< dd > < p > The name of the group variable.
Takes second column if empty.< / p > < / dd >
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< dt id = "arg-alpha" > alpha< a class = "anchor" aria-label = "anchor" href = "#arg-alpha" > < / a > < / dt >
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< dd > < p > The alpha level for the hypothesis test. Default is 0.05.< / p > < / dd >
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< dt id = "arg-beta" > beta< a class = "anchor" aria-label = "anchor" href = "#arg-beta" > < / a > < / dt >
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< dd > < p > The beta level for the sample size calculation. Default is 0.2.< / p > < / dd >
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< dt id = "arg-group-ratio" > group.ratio< a class = "anchor" aria-label = "anchor" href = "#arg-group-ratio" > < / a > < / dt >
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< dd > < p > The ratio of group sizes. Default is 1.< / p > < / dd >
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< dt id = "arg-sample-size" > sample.size< a class = "anchor" aria-label = "anchor" href = "#arg-sample-size" > < / a > < / dt >
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< dd > < p > Flag to include sample size calculation. Default is FALSE.< / p > < / dd >
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< dt id = "arg-print-tables" > print.tables< a class = "anchor" aria-label = "anchor" href = "#arg-print-tables" > < / a > < / dt >
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< dd > < p > Flag to print cumulative tables. Default is FALSE.< / p > < / dd >
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< dt id = "arg-dec" > dec< a class = "anchor" aria-label = "anchor" href = "#arg-dec" > < / a > < / dt >
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< dd > < p > Numeric for decimals to print. Default is 3.< / p > < / dd >
< / dl > < / div >
< div class = "section level2" >
< h2 id = "value" > Value< a class = "anchor" aria-label = "anchor" href = "#value" > < / a > < / h2 >
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< p > A list containing the win_prob statistics.< / p >
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< / div >
< div class = "section level2" >
< h2 id = "ref-examples" > Examples< a class = "anchor" aria-label = "anchor" href = "#ref-examples" > < / a > < / h2 >
< div class = "sourceCode" > < pre class = "sourceCode r" > < code > < span class = "r-in" > < span > < span class = "fu" > win_prob< / span > < span class = "op" > (< / span > data< span class = "op" > =< / span > < span class = "fu" > stRoke< / span > < span class = "fu" > ::< / span > < span class = "va" > < a href = "talos.html" > talos< / a > < / span > ,response< span class = "op" > =< / span > < span class = "st" > "mrs_6"< / span > ,group< span class = "op" > =< / span > < span class = "st" > "rtreat"< / span > < span class = "op" > )< / span > < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > Zou et al's winP (doi: 10.1161/STROKEAHA.121.037744) < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > Probability of a random observation in Placebo group < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > will have a higher response score than a random< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > observation in Active group:< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > winP: 0.400 (0.612, 0.372) p=0.0125< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > --------------------------------------------< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > The numbers needed to treat (NNT) are: -9< / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < / span >
< span class = "r-out co" > < span class = "r-pr" > #> < / span > < / span >
< / code > < / pre > < / div >
< / div >
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