Univariate statitstics for a variables by treatment and/or group.
Usage
univar(
df,
colvar = NULL,
tablebyvar = NULL,
rowvar = NULL,
rowbyvar = NULL,
statlist = getOption("tidytlg.univar.statlist.default"),
decimal = 1,
precisionby = NULL,
precisionon = NULL,
wide = FALSE,
alpha = 0.05,
rowtext = NULL,
row_header = NULL,
.keep = TRUE,
.ord = FALSE,
...
)Arguments
- df
(required) dataframe containing records to summarize by treatment
- colvar
(required) character vector of the treatment variable within the dataframe
- tablebyvar
(optional) repeat entire table by variable within df
- rowvar
(required) character vector of variable to summarize within the dataframe
- rowbyvar
(optional) repeat
rowvarby variable within df- statlist
(optional) statlist object of stats to keep (default = statlist(c("N", "MEANSD", "MEDIAN", "RANGE", "IQRANGE")))
- decimal
(optional) decimal precision root level, when using
presisionbythis will be used as the base decimal cap (default = 1)- precisionby
(optional) vector of by variable(s) to use when calculating parameter based precision
- precisionon
(optional) variable to use when calculating parameter based precision. If
precisionbyis specified but notprecisiononthis will default torowvar- wide
(optional) logical indicating to convert labels to column and columns to labels (default = FALSE)
- alpha
(optional) alpha level for 2-sided confidence interval (default = 0.05)
- rowtext
(optional) A text string to replace the
labelvalue on the table. Useful for tables with a single row.- row_header
(optional) A row to add as a header for the table.
- .keep
(optional) Should the
rowbyvarandtablebyvarbe output in the table. If FALSE,rowbyvarwill still be output in thelabelcolumn. (default = TRUE)- .ord
Should the ordering columns be output with the table? This is useful if a table needs to be merged or reordered in any way after build.
- ...
(optional) Named arguments to be included as columns on the table.
Examples
adsl <-
structure(
list(
USUBJID = c("DEMO-101", "DEMO-102", "DEMO-103", "DEMO-104",
"DEMO-105", "DEMO-106"),
AGE = c(59, 51, 57, 65, 21, 80),
SEX = c("F", "M", "F", "M", "F", "M"),
WEIGHTBL = c(83.6, 75, 84, 90, 65, 70),
colnbr = structure(
c(1L, 3L, 2L, 2L, 3L, 1L),
.Label = c("Placebo", "Low", "High"),
class = "factor"
)
),
row.names = c(NA, 6L),
class = "data.frame"
)
# N, Mean(SD), Median, Range, IQ Range for a rowvar by colvar
univar(adsl
,colvar = "colnbr"
,rowvar = "AGE")
#> Column Variables: colnbr
#> Row Variable: AGE
#> Statistic Formatting: N MEANSD MEDIAN RANGE IQRANGE
#> Statistic Presentation
#> Decimal Precision: 1
#> Alpha for CI Intervals: 0.05
#> Parameter Based PrecisionL None
#> # A tibble: 5 × 6
#> label Placebo Low High row_type group_level
#> * <chr> <chr> <chr> <chr> <chr> <dbl>
#> 1 N 2 2 2 N 0
#> 2 Mean (SD) 69.50 (14.849) 61.00 (5.657) 36.00 (21.213) VALUE 0
#> 3 Median 69.50 61.00 36.00 VALUE 0
#> 4 Range (59.0; 80.0) (57.0; 65.0) (21.0; 51.0) VALUE 0
#> 5 IQ range (59.00; 80.00) (57.00; 65.00) (21.00; 51.00) VALUE 0
# N and Mean for a rowvar by colvar
univar(adsl
,colvar = "colnbr"
,rowvar = "AGE"
,statlist = statlist(c("N", "MEAN")))
#> Column Variables: colnbr
#> Row Variable: AGE
#> Statistic Formatting: N MEAN
#> Statistic Presentation
#> Decimal Precision: 1
#> Alpha for CI Intervals: 0.05
#> Parameter Based PrecisionL None
#> # A tibble: 2 × 6
#> label Placebo Low High row_type group_level
#> * <chr> <chr> <chr> <chr> <chr> <dbl>
#> 1 N 2 2 2 N 0
#> 2 Mean 69.50 61.00 36.00 VALUE 0
# N and Mean for a rowvar by colvar and a by variable
univar(adsl
,colvar = "colnbr"
,rowvar = "AGE"
,rowbyvar = "SEX"
,statlist = statlist(c("N", "MEAN")))
#> Column Variables: colnbr
#> Row By Variables Variables: SEX
#> Row Variable: AGE
#> Statistic Formatting: N MEAN
#> Statistic Presentation
#> Decimal Precision: 1
#> Alpha for CI Intervals: 0.05
#> Parameter Based PrecisionL None
#> # A tibble: 6 × 7
#> SEX label Placebo Low High row_type group_level
#> * <chr> <chr> <chr> <chr> <chr> <chr> <dbl>
#> 1 F F "" "" "" BY_HEADER1 0
#> 2 F N "1" "1" "1" N 0
#> 3 F Mean "59.00" "57.00" "21.00" VALUE 0
#> 4 M M "" "" "" BY_HEADER1 0
#> 5 M N "1" "1" "1" N 0
#> 6 M Mean "80.00" "65.00" "51.00" VALUE 0
# Below illustrates how make the same calls to univar() as above, using table
# and column metadata # along with generate_results().
column_metadata <- tibble::tribble(
~tbltype, ~coldef, ~decode,
"type1", "0", "Placebo",
"type1", "54", "Low",
"type1", "81", "High"
)
# N, Mean(SD), Median, Range, IQ Range for a rowvar by colvar
table_metadata <- tibble::tribble(
~anbr, ~func, ~df, ~rowvar, ~tbltype, ~colvar,
"1", "univar", "cdisc_adae", "AGE", "type1", "TRTA"
)
generate_results(table_metadata, column_metadata = column_metadata,
tbltype = "type1")
#> # A tibble: 5 × 12
#> label col1 col2 col3 row_type func tbltype anbr indentme roworder newrows
#> * <chr> <chr> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <int> <dbl>
#> 1 N 0 0 0 N univ… type1 1 1 1 0
#> 2 Mean… - - - VALUE univ… type1 1 2 2 0
#> 3 Medi… - - - VALUE univ… type1 1 2 3 0
#> 4 Range (-; … (-; … (-; … VALUE univ… type1 1 2 4 0
#> 5 IQ r… (-; … (-; … (-; … VALUE univ… type1 1 2 5 0
#> # ℹ 1 more variable: newpage <dbl>
# N and Mean for a rowvar by colvar
table_metadata <- tibble::tribble(
~anbr, ~func, ~df, ~rowvar, ~tbltype, ~colvar, ~statlist,
"1", "univar", "cdisc_adae", "AGE", "type1", "TRTA",
statlist(c("N","MEAN"))
)
generate_results(table_metadata, column_metadata = column_metadata,
tbltype = "type1")
#> # A tibble: 2 × 12
#> label col1 col2 col3 row_type func tbltype anbr indentme roworder newrows
#> * <chr> <chr> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <int> <dbl>
#> 1 N 0 0 0 N univ… type1 1 1 1 0
#> 2 Mean - - - VALUE univ… type1 1 2 2 0
#> # ℹ 1 more variable: newpage <dbl>
# N and Mean for a rowvar by colvar and a by variable
table_metadata <- tibble::tribble(
~anbr, ~func, ~df, ~rowvar, ~tbltype, ~colvar, ~statlist, ~by,
"1", "univar", "cdisc_adae", "AGE", "type1", "TRTA",
statlist(c("N","MEAN")), "SEX"
)
generate_results(table_metadata, column_metadata = column_metadata,
tbltype = "type1")
#> # A tibble: 2 × 13
#> label col1 col2 col3 row_type func tbltype by anbr indentme roworder
#> * <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <int>
#> 1 N 0 0 0 N univar type1 SEX 1 1 1
#> 2 Mean - - - VALUE univar type1 SEX 1 2 2
#> # ℹ 2 more variables: newrows <dbl>, newpage <dbl>