Overview

freqlist() is a function meant to produce output similar to SAS’s PROC FREQ procedure when using the /list option of the TABLE statement. freqlist() provides options for handling missing or sparse data and can provide cumulative counts and percentages based on subgroups. It depends on the knitr package for printing.

require(arsenal)

Sample dataset

For our examples, we’ll load the mockstudy data included with this package and use it to create a basic table. Because they have fewer levels, for brevity, we’ll use the variables arm, sex, and mdquality.s to create the example table. We’ll retain NAs in the table creation. See the appendix for notes regarding default NA handling and other useful information regarding tables in R.

# load the data
data(mockstudy)

# retain NAs when creating the table using the useNA argument
tab.ex <- table(mockstudy[, c("arm", "sex", "mdquality.s")], useNA = "ifany")

The `freqlist` object

The freqlist() function returns an object of class "freqlist", which has three parts: freqlist, byVar, and labels.

freqlist is a single data frame containing all contingency tables with calculated frequencies, cumulative frequencies, percentages, and cumulative percentages.
byVar and labels are used in the summary method for subgroups and variable names, which will be covered in later examples.

Note that freqlist() is an S3 generic, with methods for tables and formulas.

noby <- freqlist(tab.ex)

str(noby)

List of 3
 $ freqlist:'data.frame':   18 obs. of  7 variables:
  ..$ arm        : Factor w/ 3 levels "A: IFL","F: FOLFOX",..: 1 1 1 1 1 1 2 2 2 2 ...
  ..$ sex        : Factor w/ 2 levels "Male","Female": 1 1 1 2 2 2 1 1 1 2 ...
  ..$ mdquality.s: Factor w/ 2 levels "0","1": 1 2 NA 1 2 NA 1 2 NA 1 ...
  ..$ Freq       : int [1:18] 29 214 34 12 118 21 31 285 95 21 ...
  ..$ cumFreq    : int [1:18] 29 243 277 289 407 428 459 744 839 860 ...
  ..$ freqPercent: num [1:18] 1.93 14.28 2.27 0.8 7.87 ...
  ..$ cumPercent : num [1:18] 1.93 16.21 18.48 19.28 27.15 ...
 $ byVar   : NULL
 $ labels  : NULL
 - attr(*, "class")= chr "freqlist"

# view the data frame portion of freqlist output
head(noby[["freqlist"]])  ## or use as.data.frame(noby)

     arm    sex mdquality.s Freq cumFreq freqPercent cumPercent
1 A: IFL   Male           0   29      29        1.93       1.93
2 A: IFL   Male           1  214     243       14.28      16.21
3 A: IFL   Male        <NA>   34     277        2.27      18.48
4 A: IFL Female           0   12     289        0.80      19.28
5 A: IFL Female           1  118     407        7.87      27.15
6 A: IFL Female        <NA>   21     428        1.40      28.55

Basic output using `summary()`

The summary method for freqlist() relies on the kable() function (in the knitr package) for printing. knitr::kable() converts the output to markdown which can be printed in the console or easily rendered in Word, PDF, or HTML documents.

Note that you must supply results="asis" to properly format the markdown output.

summary(noby)

arm	sex	mdquality.s	Freq	cumFreq	freqPercent	cumPercent
A: IFL	Male	0	29	29	1.93	1.93
		1	214	243	14.28	16.21
		NA	34	277	2.27	18.48
	Female	0	12	289	0.80	19.28
		1	118	407	7.87	27.15
		NA	21	428	1.40	28.55
F: FOLFOX	Male	0	31	459	2.07	30.62
		1	285	744	19.01	49.63
		NA	95	839	6.34	55.97
	Female	0	21	860	1.40	57.37
		1	198	1058	13.21	70.58
		NA	61	1119	4.07	74.65
G: IROX	Male	0	17	1136	1.13	75.78
		1	187	1323	12.47	88.26
		NA	24	1347	1.60	89.86
	Female	0	14	1361	0.93	90.79
		1	121	1482	8.07	98.87
		NA	17	1499	1.13	100.00

You can print a title for the table using the title= argument.

summary(noby, title = "Basic freqlist output")

Basic freqlist output
arm	sex	mdquality.s	Freq	cumFreq	freqPercent	cumPercent
A: IFL	Male	0	29	29	1.93	1.93
		1	214	243	14.28	16.21
		NA	34	277	2.27	18.48
	Female	0	12	289	0.80	19.28
		1	118	407	7.87	27.15
		NA	21	428	1.40	28.55
F: FOLFOX	Male	0	31	459	2.07	30.62
		1	285	744	19.01	49.63
		NA	95	839	6.34	55.97
	Female	0	21	860	1.40	57.37
		1	198	1058	13.21	70.58
		NA	61	1119	4.07	74.65
G: IROX	Male	0	17	1136	1.13	75.78
		1	187	1323	12.47	88.26
		NA	24	1347	1.60	89.86
	Female	0	14	1361	0.93	90.79
		1	121	1482	8.07	98.87
		NA	17	1499	1.13	100.00

You can also easily pull out the freqlist data frame for more complicated formatting or manipulation (e.g. with another function such as xtable() or pander()) using as.data.frame():

head(as.data.frame(noby))

     arm    sex mdquality.s Freq cumFreq freqPercent cumPercent
1 A: IFL   Male           0   29      29        1.93       1.93
2 A: IFL   Male           1  214     243       14.28      16.21
3 A: IFL   Male        <NA>   34     277        2.27      18.48
4 A: IFL Female           0   12     289        0.80      19.28
5 A: IFL Female           1  118     407        7.87      27.15
6 A: IFL Female        <NA>   21     428        1.40      28.55

Using a formula with `freqlist`

Instead of passing a pre-computed table to freqlist(), you can instead pass a formula, which will be in turn passed to the xtabs() function. Additional freqlist() arguments are passed through the ... to the freqlist() table method.

Note that the addNA= argument was added to xtabs() in R 3.4.0. In previous versions, NAs have to be added to relevant columns using addNA().

### this works in R >= 3.4.0 summary(freqlist(~ arm + sex + mdquality.s, data =
### mockstudy, addNA = TRUE))
summary(freqlist(~arm + sex + addNA(mdquality.s), data = mockstudy))



arm         sex      addNA.mdquality.s.    Freq   cumFreq   freqPercent   cumPercent
----------  -------  -------------------  -----  --------  ------------  -----------
A: IFL      Male     0                       29        29          1.93         1.93
                     1                      214       243         14.28        16.21
                     NA                      34       277          2.27        18.48
            Female   0                       12       289          0.80        19.28
                     1                      118       407          7.87        27.15
                     NA                      21       428          1.40        28.55
F: FOLFOX   Male     0                       31       459          2.07        30.62
                     1                      285       744         19.01        49.63
                     NA                      95       839          6.34        55.97
            Female   0                       21       860          1.40        57.37
                     1                      198      1058         13.21        70.58
                     NA                      61      1119          4.07        74.65
G: IROX     Male     0                       17      1136          1.13        75.78
                     1                      187      1323         12.47        88.26
                     NA                      24      1347          1.60        89.86
            Female   0                       14      1361          0.93        90.79
                     1                      121      1482          8.07        98.87
                     NA                      17      1499          1.13       100.00

Rounding percentage digits or changing variable names for printing

The digits= argument takes a single numeric value and controls the rounding of percentages in the output. The labelTranslations= argument is a character vector or list whose length must be equal to the number of factors used in the table. Note: this does not change the names of the data frame in the freqlist object, only those used in printing. Both options are applied in the following example.

withnames <- freqlist(tab.ex, labelTranslations = c("Treatment Arm", "Gender", "LASA QOL"), 
    digits = 0)
summary(withnames)

Treatment Arm	Gender	LASA QOL	Freq	cumFreq	freqPercent	cumPercent
A: IFL	Male	0	29	29	2	2
		1	214	243	14	16
		NA	34	277	2	18
	Female	0	12	289	1	19
		1	118	407	8	27
		NA	21	428	1	29
F: FOLFOX	Male	0	31	459	2	31
		1	285	744	19	50
		NA	95	839	6	56
	Female	0	21	860	1	57
		1	198	1058	13	71
		NA	61	1119	4	75
G: IROX	Male	0	17	1136	1	76
		1	187	1323	12	88
		NA	24	1347	2	90
	Female	0	14	1361	1	91
		1	121	1482	8	99
		NA	17	1499	1	100

Additional examples

Including combinations with frequencies of zero

The sparse= argument takes a single logical value as input. The default option is FALSE. If set to TRUE, the sparse option will include combinations with frequencies of zero in the list of results. As our initial table did not have any such levels, we create a second table to use in our example.

summary(freqlist(~race + sex + arm, data = mockstudy, sparse = TRUE, digits = 1))

race	sex	arm	Freq	cumFreq	freqPercent	cumPercent
African-Am	Male	A: IFL	25	25	1.7	1.7
		F: FOLFOX	24	49	1.6	3.3
		G: IROX	16	65	1.1	4.4
	Female	A: IFL	14	79	0.9	5.3
		F: FOLFOX	25	104	1.7	7.0
		G: IROX	11	115	0.7	7.7
Asian	Male	A: IFL	0	115	0.0	7.7
		F: FOLFOX	10	125	0.7	8.4
		G: IROX	1	126	0.1	8.4
	Female	A: IFL	1	127	0.1	8.5
		F: FOLFOX	4	131	0.3	8.8
		G: IROX	2	133	0.1	8.9
Caucasian	Male	A: IFL	240	373	16.1	25.0
		F: FOLFOX	352	725	23.6	48.6
		G: IROX	195	920	13.1	61.7
	Female	A: IFL	131	1051	8.8	70.4
		F: FOLFOX	234	1285	15.7	86.1
		G: IROX	136	1421	9.1	95.2
Hawaii/Pacific	Male	A: IFL	1	1422	0.1	95.3
		F: FOLFOX	1	1423	0.1	95.4
		G: IROX	0	1423	0.0	95.4
	Female	A: IFL	0	1423	0.0	95.4
		F: FOLFOX	2	1425	0.1	95.5
		G: IROX	1	1426	0.1	95.6
Hispanic	Male	A: IFL	8	1434	0.5	96.1
		F: FOLFOX	17	1451	1.1	97.3
		G: IROX	12	1463	0.8	98.1
	Female	A: IFL	4	1467	0.3	98.3
		F: FOLFOX	11	1478	0.7	99.1
		G: IROX	2	1480	0.1	99.2
Native-Am/Alaska	Male	A: IFL	1	1481	0.1	99.3
		F: FOLFOX	0	1481	0.0	99.3
		G: IROX	2	1483	0.1	99.4
	Female	A: IFL	1	1484	0.1	99.5
		F: FOLFOX	1	1485	0.1	99.5
		G: IROX	0	1485	0.0	99.5
Other	Male	A: IFL	2	1487	0.1	99.7
		F: FOLFOX	2	1489	0.1	99.8
		G: IROX	1	1490	0.1	99.9
	Female	A: IFL	0	1490	0.0	99.9
		F: FOLFOX	2	1492	0.1	100.0
		G: IROX	0	1492	0.0	100.0

Options for NA handling

The various na.options= allow you to include or exclude data with missing values for one or more factor levels in the counts and percentages, as well as show the missing data but exclude it from the cumulative counts and percentages. The default option is to include all combinations with missing values.

summary(freqlist(tab.ex, na.options = "include"))

arm	sex	mdquality.s	Freq	cumFreq	freqPercent	cumPercent
A: IFL	Male	0	29	29	1.93	1.93
		1	214	243	14.28	16.21
		NA	34	277	2.27	18.48
	Female	0	12	289	0.80	19.28
		1	118	407	7.87	27.15
		NA	21	428	1.40	28.55
F: FOLFOX	Male	0	31	459	2.07	30.62
		1	285	744	19.01	49.63
		NA	95	839	6.34	55.97
	Female	0	21	860	1.40	57.37
		1	198	1058	13.21	70.58
		NA	61	1119	4.07	74.65
G: IROX	Male	0	17	1136	1.13	75.78
		1	187	1323	12.47	88.26
		NA	24	1347	1.60	89.86
	Female	0	14	1361	0.93	90.79
		1	121	1482	8.07	98.87
		NA	17	1499	1.13	100.00

summary(freqlist(tab.ex, na.options = "showexclude"))

arm	sex	mdquality.s	Freq	cumFreq	freqPercent	cumPercent
A: IFL	Male	0	29	29	2.33	2.33
		1	214	243	17.16	19.49
		NA	34	NA	NA	NA
	Female	0	12	255	0.96	20.45
		1	118	373	9.46	29.91
		NA	21	NA	NA	NA
F: FOLFOX	Male	0	31	404	2.49	32.40
		1	285	689	22.85	55.25
		NA	95	NA	NA	NA
	Female	0	21	710	1.68	56.94
		1	198	908	15.88	72.81
		NA	61	NA	NA	NA
G: IROX	Male	0	17	925	1.36	74.18
		1	187	1112	15.00	89.17
		NA	24	NA	NA	NA
	Female	0	14	1126	1.12	90.30
		1	121	1247	9.70	100.00
		NA	17	NA	NA	NA

summary(freqlist(tab.ex, na.options = "remove"))

arm	sex	mdquality.s	Freq	cumFreq	freqPercent	cumPercent
A: IFL	Male	0	29	29	2.33	2.33
		1	214	243	17.16	19.49
	Female	0	12	255	0.96	20.45
		1	118	373	9.46	29.91
F: FOLFOX	Male	0	31	404	2.49	32.40
		1	285	689	22.85	55.25
	Female	0	21	710	1.68	56.94
		1	198	908	15.88	72.81
G: IROX	Male	0	17	925	1.36	74.18
		1	187	1112	15.00	89.17
	Female	0	14	1126	1.12	90.30
		1	121	1247	9.70	100.00

Frequency counts and percentages subset by factor levels

The groupBy= argument internally subsets the data by the specified factor prior to calculating cumulative counts and percentages. By default, when used each subset will print in a separate table. Using the single = TRUE option when printing will collapse the subsetted result into a single table.

withby <- freqlist(tab.ex, groupBy = c("arm", "sex"))
summary(withby)

arm	sex	mdquality.s	Freq	cumFreq	freqPercent	cumPercent
A: IFL	Male	0	29	29	10.47	10.47
		1	214	243	77.26	87.73
		NA	34	277	12.27	100.00

arm	sex	mdquality.s	Freq	cumFreq	freqPercent	cumPercent
A: IFL	Female	0	12	12	7.95	7.95
		1	118	130	78.15	86.09
		NA	21	151	13.91	100.00

arm	sex	mdquality.s	Freq	cumFreq	freqPercent	cumPercent
F: FOLFOX	Male	0	31	31	7.54	7.54
		1	285	316	69.34	76.89
		NA	95	411	23.11	100.00

arm	sex	mdquality.s	Freq	cumFreq	freqPercent	cumPercent
F: FOLFOX	Female	0	21	21	7.50	7.50
		1	198	219	70.71	78.21
		NA	61	280	21.79	100.00

arm	sex	mdquality.s	Freq	cumFreq	freqPercent	cumPercent
G: IROX	Male	0	17	17	7.46	7.46
		1	187	204	82.02	89.47
		NA	24	228	10.53	100.00

arm	sex	mdquality.s	Freq	cumFreq	freqPercent	cumPercent
G: IROX	Female	0	14	14	9.21	9.21
		1	121	135	79.61	88.82
		NA	17	152	11.18	100.00

# using the single = TRUE argument will collapse results into a single table for
# printing
summary(withby, single = TRUE)

arm	sex	mdquality.s	Freq	cumFreq	freqPercent	cumPercent
A: IFL	Male	0	29	29	10.47	10.47
		1	214	243	77.26	87.73
		NA	34	277	12.27	100.00
	Female	0	12	12	7.95	7.95
		1	118	130	78.15	86.09
		NA	21	151	13.91	100.00
F: FOLFOX	Male	0	31	31	7.54	7.54
		1	285	316	69.34	76.89
		NA	95	411	23.11	100.00
	Female	0	21	21	7.50	7.50
		1	198	219	70.71	78.21
		NA	61	280	21.79	100.00
G: IROX	Male	0	17	17	7.46	7.46
		1	187	204	82.02	89.47
		NA	24	228	10.53	100.00
	Female	0	14	14	9.21	9.21
		1	121	135	79.61	88.82
		NA	17	152	11.18	100.00

Change labels on the fly

At this time, the labels can be changed just for the variables (e.g. not the frequency columns).

labels(noby) <- c("Arm", "Sex", "QOL")
summary(noby)

Arm	Sex	QOL	Freq	cumFreq	freqPercent	cumPercent
A: IFL	Male	0	29	29	1.93	1.93
		1	214	243	14.28	16.21
		NA	34	277	2.27	18.48
	Female	0	12	289	0.80	19.28
		1	118	407	7.87	27.15
		NA	21	428	1.40	28.55
F: FOLFOX	Male	0	31	459	2.07	30.62
		1	285	744	19.01	49.63
		NA	95	839	6.34	55.97
	Female	0	21	860	1.40	57.37
		1	198	1058	13.21	70.58
		NA	61	1119	4.07	74.65
G: IROX	Male	0	17	1136	1.13	75.78
		1	187	1323	12.47	88.26
		NA	24	1347	1.60	89.86
	Female	0	14	1361	0.93	90.79
		1	121	1482	8.07	98.87
		NA	17	1499	1.13	100.00

You can also supply labelTranslations= to summary().

summary(noby, labelTranslations = c("Arm", "Sex", "QOL"))

Arm	Sex	QOL	Freq	cumFreq	freqPercent	cumPercent
A: IFL	Male	0	29	29	1.93	1.93
		1	214	243	14.28	16.21
		NA	34	277	2.27	18.48
	Female	0	12	289	0.80	19.28
		1	118	407	7.87	27.15
		NA	21	428	1.40	28.55
F: FOLFOX	Male	0	31	459	2.07	30.62
		1	285	744	19.01	49.63
		NA	95	839	6.34	55.97
	Female	0	21	860	1.40	57.37
		1	198	1058	13.21	70.58
		NA	61	1119	4.07	74.65
G: IROX	Male	0	17	1136	1.13	75.78
		1	187	1323	12.47	88.26
		NA	24	1347	1.60	89.86
	Female	0	14	1361	0.93	90.79
		1	121	1482	8.07	98.87
		NA	17	1499	1.13	100.00

Using `xtable()` to format and print `freqlist()` results

Fair warning: xtable() has kind of a steep learning curve. These examples are given without explanation, for more advanced users.

require(xtable)

Loading required package: xtable

# set up custom function for xtable text
italic <- function(x) {
    paste0("<i>", x, "</i>")
}

xftbl <- xtable(noby[["freqlist"]], caption = "xtable formatted output of freqlist data frame", 
    align = "|r|r|r|r|c|c|c|r|")

# change the column names
names(xftbl)[1:3] <- c("Arm", "Gender", "LASA QOL")

print(xftbl, sanitize.colnames.function = italic, include.rownames = FALSE, type = "html", 
    comment = FALSE)

xtable formatted output of freqlist data frame
Arm	Gender	LASA QOL	Freq	cumFreq	freqPercent	cumPercent
A: IFL	Male	0	29	29	1.93	1.93
A: IFL	Male	1	214	243	14.28	16.21
A: IFL	Male		34	277	2.27	18.48
A: IFL	Female	0	12	289	0.80	19.28
A: IFL	Female	1	118	407	7.87	27.15
A: IFL	Female		21	428	1.40	28.55
F: FOLFOX	Male	0	31	459	2.07	30.62
F: FOLFOX	Male	1	285	744	19.01	49.63
F: FOLFOX	Male		95	839	6.34	55.97
F: FOLFOX	Female	0	21	860	1.40	57.37
F: FOLFOX	Female	1	198	1058	13.21	70.58
F: FOLFOX	Female		61	1119	4.07	74.65
G: IROX	Male	0	17	1136	1.13	75.78
G: IROX	Male	1	187	1323	12.47	88.26
G: IROX	Male		24	1347	1.60	89.86
G: IROX	Female	0	14	1361	0.93	90.79
G: IROX	Female	1	121	1482	8.07	98.87
G: IROX	Female		17	1499	1.13	100.00

Appendix: Notes regarding table options in R

NAs

There are several widely used options for basic tables in R. The table() function in base R is probably the most common; by default it excludes NA values. You can change NA handling in base::table() using the useNA= or exclude= arguments.

# base table default removes NAs
tab.d1 <- base::table(mockstudy[, c("arm", "sex", "mdquality.s")], useNA = "ifany")
tab.d1

, , mdquality.s = 0

           sex
arm         Male Female
  A: IFL      29     12
  F: FOLFOX   31     21
  G: IROX     17     14

, , mdquality.s = 1

           sex
arm         Male Female
  A: IFL     214    118
  F: FOLFOX  285    198
  G: IROX    187    121

, , mdquality.s = NA

           sex
arm         Male Female
  A: IFL      34     21
  F: FOLFOX   95     61
  G: IROX     24     17

xtabs() is similar to table(), but uses a formula-based syntax. However, there is not an option for retaining NAs in the xtabs() function; instead, NAs must be added to each level of the factor where present using the addNA() function, or (in R >= 3.4.0) using the argument addNA = TRUE.

# without specifying addNA
tab.d2 <- xtabs(formula = ~arm + sex + mdquality.s, data = mockstudy)
tab.d2

, , mdquality.s = 0

           sex
arm         Male Female
  A: IFL      29     12
  F: FOLFOX   31     21
  G: IROX     17     14

, , mdquality.s = 1

           sex
arm         Male Female
  A: IFL     214    118
  F: FOLFOX  285    198
  G: IROX    187    121

# now with addNA
tab.d3 <- xtabs(~arm + sex + addNA(mdquality.s), data = mockstudy)
tab.d3

, , addNA(mdquality.s) = 0

           sex
arm         Male Female
  A: IFL      29     12
  F: FOLFOX   31     21
  G: IROX     17     14

, , addNA(mdquality.s) = 1

           sex
arm         Male Female
  A: IFL     214    118
  F: FOLFOX  285    198
  G: IROX    187    121

, , addNA(mdquality.s) = NA

           sex
arm         Male Female
  A: IFL      34     21
  F: FOLFOX   95     61
  G: IROX     24     17

Since the formula method of freqlist() uses xtabs(), NAs should be treated in the same way.

Table dimname names (dnn)

Supplying a data.frame to the table() function without giving columns individually will create a contingency table using all variables in the data.frame.

However, if the columns of a data.frame or matrix are supplied separately (i.e., as vectors), column names will not be preserved.

# providing variables separately (as vectors) drops column names
tab.d4 <- base::table(mockstudy$arm, mockstudy$sex, mockstudy$mdquality.s)
tab.d4

, ,  = 0

           
            Male Female
  A: IFL      29     12
  F: FOLFOX   31     21
  G: IROX     17     14

, ,  = 1

           
            Male Female
  A: IFL     214    118
  F: FOLFOX  285    198
  G: IROX    187    121

If desired, you can use the dnn= argument to pass variable names.

# add the column name labels back using dnn option in base::table
tab.dnn <- base::table(mockstudy$arm, mockstudy$sex, mockstudy$mdquality.s, dnn = c("Arm", 
    "Sex", "QOL"))
tab.dnn

, , QOL = 0

           Sex
Arm         Male Female
  A: IFL      29     12
  F: FOLFOX   31     21
  G: IROX     17     14

, , QOL = 1

           Sex
Arm         Male Female
  A: IFL     214    118
  F: FOLFOX  285    198
  G: IROX    187    121

If using freqlist(), you can provide the labels directly to freqlist() or to summary() using labelTranslations=.

The freqlist function

Tina Gunderson and Ethan Heinzen

02 February, 2018

Overview

Sample dataset

The `freqlist` object

Basic output using `summary()`

Using a formula with `freqlist`

Rounding percentage digits or changing variable names for printing

Additional examples

Including combinations with frequencies of zero

Options for NA handling

Frequency counts and percentages subset by factor levels

Change labels on the fly

Using `xtable()` to format and print `freqlist()` results

Appendix: Notes regarding table options in R

NAs

Table dimname names (dnn)

The freqlist function

Tina Gunderson and Ethan Heinzen

02 February, 2018

Overview

Sample dataset

The freqlist object

Basic output using summary()

Using a formula with freqlist

Rounding percentage digits or changing variable names for printing

Additional examples

Including combinations with frequencies of zero

Options for NA handling

Frequency counts and percentages subset by factor levels

Change labels on the fly

Using xtable() to format and print freqlist() results

Appendix: Notes regarding table options in R

NAs

Table dimname names (dnn)

The `freqlist` object

Basic output using `summary()`

Using a formula with `freqlist`

Using `xtable()` to format and print `freqlist()` results