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AWKruijt / JT-RCI

obtain and plot Jacobson-Truax and reliable change indices
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Error: unused arguments #3

Open chris-gaskell opened 3 years ago

chris-gaskell commented 3 years ago

Thank you for providing this excellent resource. It is EXACTLY what I have been looking for. I was hoping you could help me with the following. I am not sure if it is a bug with the package or (more likely) I am doing something wrong.

I am having a problem with running the example code. I have installed the package via devtools and run your example code (below) however it returns the error ' Error in JTRCI(data = df, pre = "pre", post = "post", group = "group", : unused arguments (data = df, pre = "pre", post = "post", group = "group", indextype = "RCI")

Code used: df <- cbind.data.frame("ppid" = seq(1:64), "pre" = rnorm(64, 65, 8), "post" = c(rnorm(32, 40, 8), rnorm(32, 45, 8)), "group" = rep(c("treatment", "control"), each = 32))

JTRCI(data = df, 
      ppid = "ppid", 
      pre = "pre", 
      post = "post",  
      reliability = .8, 
      indextype = "JT", 
      JTcrit = "auto")

Truly appreciate any help you can provide

milanwiedemann commented 3 years ago

I just tried your example code and it seems to work fine for me, see repex below. If you're still having problems running the code, could you send more information about your R session (e.g., version number of R, version number of packages)?

library(JTRCI)

df <- cbind.data.frame("ppid" = seq(1:64),
                       "pre" = rnorm(64, 65, 8),
                       "post" = c(rnorm(32, 40, 8), rnorm(32, 45, 8)),
                       "group" = rep(c("treatment", "control"), each = 32))

JTRCI(data = df, 
      ppid = "ppid", 
      pre = "pre", 
      post = "post",  
      reliability = .8, 
      indextype = "JT", 
      JTcrit = "auto")
#> Assumed that lower scores are better (and reduction == improvement),
#>  if that is incorrect: set higherIsBetter = T
#> NB: using the sample baseline distribution to characterize the dysfunctional population. 
#>     to change: provide norms for dysfunctional population using 'dysfM =' and 'dysfSD ='
#> Jacobson-Truax criterion A: 46.9
#>  this value represents two sd from the baseline  sample mean
#> 1 participants scored below the Jacobson-Truax cut-off score at the pre-measurement 
#>  interpret their Jacobson-Truax classification with caution
#> Loading required package: data.table
#>    Jacobson-Truax classification  N
#> 1:                  deteriorated  0
#> 2:                     unchanged 17
#> 3:                      improved 12
#> 4:        non reliably recovered  4
#> 5:                     recovered 31

Created on 2021-01-21 by the reprex package (v0.3.0)

Session info ``` r devtools::session_info() #> ─ Session info ─────────────────────────────────────────────────────────────── #> setting value #> version R version 4.0.2 (2020-06-22) #> os macOS 10.16 #> system x86_64, darwin17.0 #> ui X11 #> language (EN) #> collate en_GB.UTF-8 #> ctype en_GB.UTF-8 #> tz Europe/Tallinn #> date 2021-01-21 #> #> ─ Packages ─────────────────────────────────────────────────────────────────── #> package * version date lib source #> assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.0.0) #> callr 3.5.1 2020-10-13 [1] CRAN (R 4.0.2) #> cli 2.2.0 2020-11-20 [1] CRAN (R 4.0.2) #> colorspace 2.0-0 2020-11-11 [1] CRAN (R 4.0.2) #> crayon 1.3.4 2017-09-16 [1] CRAN (R 4.0.0) #> curl 4.3 2019-12-02 [1] CRAN (R 4.0.0) #> data.table * 1.13.4 2020-12-08 [1] CRAN (R 4.0.2) #> desc 1.2.0 2018-05-01 [1] CRAN (R 4.0.0) #> devtools 2.3.2 2020-09-18 [1] CRAN (R 4.0.2) #> digest 0.6.27 2020-10-24 [1] CRAN (R 4.0.2) #> dplyr 1.0.2 2020-08-18 [1] CRAN (R 4.0.2) #> ellipsis 0.3.1 2020-05-15 [1] CRAN (R 4.0.0) #> evaluate 0.14 2019-05-28 [1] CRAN (R 4.0.0) #> fansi 0.4.1 2020-01-08 [1] CRAN (R 4.0.0) #> farver 2.0.3 2020-01-16 [1] CRAN (R 4.0.0) #> fs 1.5.0 2020-07-31 [1] CRAN (R 4.0.2) #> generics 0.1.0 2020-10-31 [1] CRAN (R 4.0.2) #> ggplot2 * 3.3.2 2020-06-19 [1] CRAN (R 4.0.0) #> glue 1.4.2 2020-08-27 [1] CRAN (R 4.0.2) #> gtable 0.3.0 2019-03-25 [1] CRAN (R 4.0.0) #> highr 0.8 2019-03-20 [1] CRAN (R 4.0.0) #> htmltools 0.5.0 2020-06-16 [1] CRAN (R 4.0.0) #> httr 1.4.2 2020-07-20 [1] CRAN (R 4.0.2) #> JTRCI * 0.1.0 2020-06-29 [1] local #> knitr 1.30 2020-09-22 [1] CRAN (R 4.0.2) #> labeling 0.4.2 2020-10-20 [1] CRAN (R 4.0.2) #> lifecycle 0.2.0 2020-03-06 [1] CRAN (R 4.0.0) #> magrittr 2.0.1 2020-11-17 [1] CRAN (R 4.0.2) #> memoise 1.1.0 2017-04-21 [1] CRAN (R 4.0.0) #> mime 0.9 2020-02-04 [1] CRAN (R 4.0.0) #> munsell 0.5.0 2018-06-12 [1] CRAN (R 4.0.0) #> pillar 1.4.7 2020-11-20 [1] CRAN (R 4.0.2) #> pkgbuild 1.2.0 2020-12-15 [1] CRAN (R 4.0.2) #> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.0.0) #> pkgload 1.1.0 2020-05-29 [1] CRAN (R 4.0.0) #> prettyunits 1.1.1 2020-01-24 [1] CRAN (R 4.0.0) #> processx 3.4.5 2020-11-30 [1] CRAN (R 4.0.2) #> ps 1.5.0 2020-12-05 [1] CRAN (R 4.0.2) #> purrr 0.3.4 2020-04-17 [1] CRAN (R 4.0.0) #> R6 2.5.0 2020-10-28 [1] CRAN (R 4.0.2) #> remotes 2.2.0 2020-07-21 [1] CRAN (R 4.0.2) #> rlang 0.4.9 2020-11-26 [1] CRAN (R 4.0.2) #> rmarkdown 2.6 2020-12-14 [1] CRAN (R 4.0.2) #> rprojroot 2.0.2 2020-11-15 [1] CRAN (R 4.0.2) #> scales 1.1.1 2020-05-11 [1] CRAN (R 4.0.0) #> sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 4.0.0) #> stringi 1.5.3 2020-09-09 [1] CRAN (R 4.0.2) #> stringr 1.4.0 2019-02-10 [1] CRAN (R 4.0.0) #> testthat 3.0.1 2020-12-17 [1] CRAN (R 4.0.2) #> tibble 3.0.4.9000 2020-11-19 [1] Github (tidyverse/tibble@9eeef4d) #> tidyselect 1.1.0 2020-05-11 [1] CRAN (R 4.0.0) #> usethis 2.0.0 2020-12-10 [1] CRAN (R 4.0.2) #> vctrs 0.3.6 2020-12-17 [1] CRAN (R 4.0.2) #> withr 2.3.0 2020-09-22 [1] CRAN (R 4.0.2) #> xfun 0.19 2020-10-30 [1] CRAN (R 4.0.2) #> xml2 1.3.2 2020-04-23 [1] CRAN (R 4.0.0) #> yaml 2.2.1 2020-02-01 [1] CRAN (R 4.0.0) #> #> [1] /Library/Frameworks/R.framework/Versions/4.0/Resources/library ```
chris-gaskell commented 3 years ago

Dear Milan Wiedemann

Thank you so much for your kind reply. Very strange, but not that I just re-attempted the code it seems to now work first time.

Thanks Milan

Excellent package by the way

Chris

Christopher Gaskell Trainee Clinical Psychologist University of Sheffield

On 21 Jan 2021, at 11:43, Milan Wiedemann notifications@github.com wrote:

I just tried your example code and it seems to work fine for me, see repex below. If you're still having problems running the code, could you send more information about your R session (e.g., version number of R, version number of packages)?

library(JTRCI)

df <- cbind.data.frame("ppid" = seq(1:64), "pre" = rnorm(64, 65, 8), "post" = c(rnorm(32, 40, 8), rnorm(32, 45, 8)), "group" = rep(c("treatment", "control"), each = 32))

JTRCI(data = df, ppid = "ppid", pre = "pre", post = "post",
reliability = .8, indextype = "JT", JTcrit = "auto")

> Assumed that lower scores are better (and reduction == improvement),

> if that is incorrect: set higherIsBetter = T

> NB: using the sample baseline distribution to characterize the dysfunctional population.

> to change: provide norms for dysfunctional population using 'dysfM =' and 'dysfSD ='

> Jacobson-Truax criterion A: 46.9

> this value represents two sd from the baseline sample mean

> 1 participants scored below the Jacobson-Truax cut-off score at the pre-measurement

> interpret their Jacobson-Truax classification with caution

> Loading required package: data.table

> Jacobson-Truax classification N

> 1: deteriorated 0

> 2: unchanged 17

> 3: improved 12

> 4: non reliably recovered 4

> 5: recovered 31

https://camo.githubusercontent.com/3d7ab0a762919a2bd15244814ad793139097822ac7079259630c7d6d75bf5a6d/68747470733a2f2f692e696d6775722e636f6d2f3958784468756b2e706e67 Created on 2021-01-21 by the reprex package https://reprex.tidyverse.org/ (v0.3.0)

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