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summarizeByVisitSCI

Source: vignettes/summarizeByVisitSCI.Rmd
summarizeByVisitSCI.Rmd

summarizeByVisitSCI() is the counterpart of summarizeSCI() for data collected over several visits. It produces the table of summaryByVisit() and one plot per variable over the visits: a line plot (or boxplots) for continuous variables and stacked barplots for categorical ones.

Setup and data 

library(summarySCI)
data(hemoglobin_data)

hb <- hemoglobin_data
hb$hb_cat <- cut(hb$hb, c(-Inf, 120, 140, Inf),
                 labels = c("< 120", "120-140", "> 140"))

Table and plots

The arguments are those of summaryByVisit(). The visits appear in the order of the table; with order, its values also set the spacing of the visits in the line plot.

res <- summarizeByVisitSCI(hb, vars = c("hb", "hb_cat"), group = "Arm",
                           visit = "visit", order = "visit_nr",
                           stat_cont = "median_IQR",
                           labels = list(hb_cat = "Hemoglobin category"),
                           plot_args = list(risk_table = TRUE,
                                            group_names_short = c("A", "B")))
res$table

Visit

N1

Arm A
N = 842

N1

Arm B
N = 852

Hemoglobin

Cycle 1

29

130.0 (127.0, 138.0)

23

132.0 (120.0, 139.0)

Cycle 2

83

135.0 (127.0, 140.0)

84

133.0 (122.5, 139.0)

Cycle 3

83

136.0 (129.0, 143.0)

80

131.5 (124.0, 141.5)

Cycle 4

80

136.0 (128.5, 141.0)

73

133.0 (124.0, 138.0)

Cycle 5

71

137.0 (128.0, 142.0)

65

131.0 (124.0, 138.0)

Cycle 6

69

137.0 (131.0, 143.0)

62

131.0 (124.0, 137.0)

Cycle 7

65

137.0 (129.0, 142.0)

62

130.0 (123.0, 138.0)

Cycle 8

60

136.0 (131.5, 141.5)

62

130.0 (124.0, 139.0)

Cycle 9

62

136.5 (130.0, 140.0)

60

131.0 (124.0, 136.5)

Hemoglobin category

Cycle 1

29

23

< 120

5 (6%)

7 (8%)

120-140

18 (21%)

12 (14%)

> 140

6 (7%)

4 (5%)

Missing

55 (65%)

62 (73%)

Cycle 2

83

84

< 120

8 (10%)

18 (21%)

120-140

55 (66%)

49 (58%)

> 140

20 (24%)

17 (20%)

Missing

0 (0%)

1 (1%)

Cycle 3

83

80

< 120

6 (7%)

12 (15%)

120-140

49 (59%)

47 (57%)

> 140

28 (34%)

21 (26%)

Missing

0 (0%)

2 (2%)

Cycle 4

80

73

< 120

8 (10%)

15 (20%)

120-140

49 (61%)

46 (62%)

> 140

23 (29%)

12 (16%)

Missing

0 (0%)

1 (1%)

Cycle 5

71

65

< 120

5 (7%)

9 (13%)

120-140

43 (59%)

45 (67%)

> 140

23 (32%)

11 (16%)

Missing

2 (3%)

2 (3%)

Cycle 6

69

62

< 120

2 (3%)

9 (14%)

120-140

42 (61%)

46 (71%)

> 140

25 (36%)

7 (11%)

Missing

0 (0%)

3 (5%)

Cycle 7

65

62

< 120

5 (8%)

7 (11%)

120-140

37 (57%)

44 (70%)

> 140

23 (35%)

11 (17%)

Missing

0 (0%)

1 (2%)

Cycle 8

60

62

< 120

4 (6%)

9 (15%)

120-140

38 (59%)

42 (68%)

> 140

18 (28%)

11 (18%)

Missing

4 (6%)

0 (0%)

Cycle 9

62

60

< 120

3 (5%)

7 (12%)

120-140

44 (70%)

46 (77%)

> 140

15 (24%)

7 (12%)

Missing

1 (2%)

0 (0%)

1N without missing values

2Median (Q1, Q3); n (%)

 
res$plots$hb

res$plots$hb_cat

As in summarizeSCI(), type = "table" or "plot" returns only one of them, the table’s settings (labels, missing, missing_percent, stat_cat) carry over to the plots, and further plot options go into plot_args (see ?lineplotSCI, ?boxplotSCI and ?stackedbarplotSCI).

The plots show the numbers of the table

The line plots and stacked bars are drawn from the numbers printed in the table, as plotByVisit() does: they show exactly what the table shows, with its rounding, its visits and its N columns as the risk table. stat_cont decides what the line plot shows:

stat_cont Point Error bars
"median_range" median minimum to maximum
"median_IQR" median first to third quartile
"mean_sd" mean +/- one standard deviation
"mean_se" mean +/- one standard error
"geomMean_sd" geometric mean ÷ and × geometric SD

The geometric mean needs positive values: the table shows NA for visits with values of zero or below, and the line plot leaves those points out. plot_args = list(stat_footnote = TRUE) names the statistic in a footnote under each plot.

plot_cont = "boxplot" draws boxplots per visit instead of the line plot. A boxplot shows more than the table holds, so it is drawn from the data: from the rows the table summarizes, with the box at the quartiles as the table computes them. It always shows the median and quartiles, whatever stat_cont the table uses; with "median_IQR" the two agree.

res_box <- summarizeByVisitSCI(hb, vars = "hb", group = "Arm",
                               visit = "visit", order = "visit_nr",
                               stat_cont = "mean_sd", plot_cont = "boxplot",
                               plot_args = list(cex_axis = 0.8))
res_box$plots$hb

Saving the table and plots

word_output = TRUE (with file_path) and save_plots() work as described in vignette("summarizeSCI"):

basename(save_plots(res, file_name = "visit", file_path = tempdir(),
                    width = 9, height = 5.5))
#> [1] "visit_hb.png"     "visit_hb_cat.png"