add.stat.Rdadd.stat.desc
enables to add a specific quantitative statistic into an existing table of statistics.
add.stat(tab, data, func.stat, func.stat.name, pos, ...) # S3 method for desc add.stat(tab, data, func.stat, func.stat.name, pos = NULL, ...)
| tab | A desc object |
|---|---|
| data | The data frame used to create tab |
| func.stat | Passed to |
| func.stat.name | Passed to |
| pos | Numeric used to specify the position of the new statistics |
| ... | Other parameters |
A "quanti" desc object (desc$type.desc equal to "quanti")
Add a specific statistic in a desc object (only works for quantitative statistics for now).
It calls the report.quanti function with the same attributes as the tab argument and
uses the regroup function to bind the two results.
# Load the data data(datafake) # The default statistics are given here: tab1=report.quanti(data=datafake,y="y_numeric",x1="GROUP",total=TRUE,subjid="SUBJID") # Define the function corresponding to the coefficient of variation for example cv=function(y) sd(y,na.rm=TRUE)/mean(y,na.rm=TRUE) # We use the add.stat function to add CV at the second row: tab1.cv=add.stat(tab1,datafake,func.stat=cv,func.stat.name="Coef. Var", pos=2) tab1.cv#> #> ############################################ #> #> ############################################ #> #> Statistics A (N=30) B (N=21) C (N=17) Total (N=68) #> 6 N 180 120 96 396 #> 11 Coef. Var 1.03 0.64 0.65 0.86 #> 3 Mean (SD) 1.46(1.50) 3.15(2.00) 3.87(2.52) 2.56(2.20) #> 4 Median 1.59 3.75 4.73 2.71 #> 2 [Q1;Q3] [0.45;2.50] [2.46;4.44] [3.44;5.30] [1.04;4.33] #> 1 [Min;Max] [-2.34;4.36] [-2.44;6.19] [-2.99;7.96] [-2.99;7.96] #> 5 Missing 4 4 2 10 #> #> ############################################ #># Same with 2 explicative variables tab=report.quanti(data=datafake,y="y_numeric",x1="GROUP", x2="TIMEPOINT",total=TRUE,subjid="SUBJID", at.row="TIMEPOINT") tab=add.stat(tab,datafake,func.stat=cv,func.stat.name="Coef. Var", pos=2) tab#> #> ############################################ #> #> ############################################ #> #> TIMEPOINT Statistics A (N=30) B (N=21) C (N=17) Total (N=68) #> 1 D0 N 30 20 16 66 #> 2 D0 Coef. Var -0.92 -1.62 -0.78 -1.04 #> 3 D0 Mean (SD) -0.93(0.86) -0.67(1.09) -1.19(0.92) -0.92(0.95) #> 4 D0 Median -0.82 -0.69 -1.26 -0.86 #> 5 D0 [Q1;Q3] [-1.59;-0.16] [-1.39;-0.06] [-1.62;-0.83] [-1.55;-0.16] #> 6 D0 [Min;Max] [-2.34;0.36] [-2.44;2.10] [-2.99;0.66] [-2.99;2.10] #> 7 D0 Missing 1 1 0 2 #> 8 #> 9 D1 N 30 20 16 66 #> 10 D1 Coef. Var 0.57 0.31 0.14 0.52 #> 11 D1 Mean (SD) 1.83(1.04) 4.17(1.28) 4.98(0.69) 3.33(1.73) #> 12 D1 Median 1.78 4.19 5.08 3.57 #> 13 D1 [Q1;Q3] [ 0.94; 2.54] [ 3.23; 4.92] [ 4.58; 5.46] [ 1.78; 4.91] #> 14 D1 [Min;Max] [ 0.11;3.88] [ 1.48;6.19] [ 3.80;6.23] [ 0.11;6.23] #> 15 D1 Missing 1 0 0 1 #> 16 #> 17 D2 N 30 20 16 66 #> 18 D2 Coef. Var 0.60 0.22 0.28 0.51 #> 19 D2 Mean (SD) 1.97(1.17) 4.04(0.89) 4.90(1.36) 3.32(1.70) #> 20 D2 Median 1.66 4.19 5.06 3.57 #> 21 D2 [Q1;Q3] [ 1.23; 2.86] [ 3.62; 4.36] [ 4.34; 5.20] [ 1.89; 4.44] #> 22 D2 [Min;Max] [-0.18;4.36] [ 2.03;5.63] [ 2.39;7.96] [-0.18;7.96] #> 23 D2 Missing 1 1 0 2 #> 24 #> 25 D3 N 30 20 16 66 #> 26 D3 Coef. Var 0.66 0.25 0.22 0.56 #> 27 D3 Mean (SD) 1.78(1.17) 3.81(0.94) 5.07(1.12) 3.15(1.75) #> 28 D3 Median 1.78 3.63 5.22 3.15 #> 29 D3 [Q1;Q3] [ 0.93; 2.42] [ 3.13; 4.44] [ 4.11; 5.66] [ 1.80; 4.39] #> 30 D3 [Min;Max] [-0.16;3.90] [ 2.46;6.01] [ 3.16;7.37] [-0.16;7.37] #> 31 D3 Missing 0 1 1 2 #> 32 #> 33 D4 N 30 20 16 66 #> 34 D4 Coef. Var 0.46 0.25 0.20 0.52 #> 35 D4 Mean (SD) 1.83(0.85) 3.80(0.95) 5.17(1.03) 3.22(1.66) #> 36 D4 Median 1.67 3.83 4.88 3.16 #> 37 D4 [Q1;Q3] [ 1.26; 2.32] [ 3.12; 4.42] [ 4.69; 5.50] [ 1.69; 4.48] #> 38 D4 [Min;Max] [ 0.38;3.97] [ 2.31;5.41] [ 3.24;6.96] [ 0.38;6.96] #> 39 D4 Missing 1 1 1 3 #> 40 #> 41 D5 N 30 20 16 66 #> 42 D5 Coef. Var 0.53 0.33 0.22 0.45 #> 43 D5 Mean (SD) 2.27(1.20) 3.64(1.19) 4.43(0.98) 3.21(1.45) #> 44 D5 Median 2.50 3.86 4.57 3.28 #> 45 D5 [Q1;Q3] [ 1.77; 3.21] [ 2.59; 4.60] [ 3.44; 4.97] [ 2.42; 4.44] #> 46 D5 [Min;Max] [-1.19;4.31] [ 0.91;5.12] [ 2.95;6.54] [-1.19;6.54] #> 47 D5 Missing 0 0 0 0 #> #> ############################################ #># And on position 5, we can add for example the mode mode=function(x) { x=na.omit(x) ux <- unique(x) ux[which.max(tabulate(match(x, ux)))] } tab=add.stat(tab,datafake,func.stat=mode,func.stat.name="Mode", pos=5) tab#> #> ############################################ #> #> ############################################ #> #> TIMEPOINT Statistics A (N=30) B (N=21) C (N=17) Total (N=68) #> 1 D0 N 30 20 16 66 #> 2 D0 Coef. Var -0.92 -1.62 -0.78 -1.04 #> 3 D0 Mean (SD) -0.93(0.86) -0.67(1.09) -1.19(0.92) -0.92(0.95) #> 4 D0 Median -0.82 -0.69 -1.26 -0.86 #> 5 D0 Mode -0.42 -0.36 -0.75 -0.42 #> 6 D0 [Q1;Q3] [-1.59;-0.16] [-1.39;-0.06] [-1.62;-0.83] [-1.55;-0.16] #> 7 D0 [Min;Max] [-2.34;0.36] [-2.44;2.10] [-2.99;0.66] [-2.99;2.10] #> 8 D0 Missing 1 1 0 2 #> 9 #> 10 D1 N 30 20 16 66 #> 11 D1 Coef. Var 0.57 0.31 0.14 0.52 #> 12 D1 Mean (SD) 1.83(1.04) 4.17(1.28) 4.98(0.69) 3.33(1.73) #> 13 D1 Median 1.78 4.19 5.08 3.57 #> 14 D1 Mode 3.88 5.71 5.02 3.88 #> 15 D1 [Q1;Q3] [ 0.94; 2.54] [ 3.23; 4.92] [ 4.58; 5.46] [ 1.78; 4.91] #> 16 D1 [Min;Max] [ 0.11;3.88] [ 1.48;6.19] [ 3.80;6.23] [ 0.11;6.23] #> 17 D1 Missing 1 0 0 1 #> 18 #> 19 D2 N 30 20 16 66 #> 20 D2 Coef. Var 0.60 0.22 0.28 0.51 #> 21 D2 Mean (SD) 1.97(1.17) 4.04(0.89) 4.90(1.36) 3.32(1.70) #> 22 D2 Median 1.66 4.19 5.06 3.57 #> 23 D2 Mode 1.35 4.35 6.58 1.35 #> 24 D2 [Q1;Q3] [ 1.23; 2.86] [ 3.62; 4.36] [ 4.34; 5.20] [ 1.89; 4.44] #> 25 D2 [Min;Max] [-0.18;4.36] [ 2.03;5.63] [ 2.39;7.96] [-0.18;7.96] #> 26 D2 Missing 1 1 0 2 #> 27 #> 28 D3 N 30 20 16 66 #> 29 D3 Coef. Var 0.66 0.25 0.22 0.56 #> 30 D3 Mean (SD) 1.78(1.17) 3.81(0.94) 5.07(1.12) 3.15(1.75) #> 31 D3 Median 1.78 3.63 5.22 3.15 #> 32 D3 Mode 2.54 4.44 5.66 2.54 #> 33 D3 [Q1;Q3] [ 0.93; 2.42] [ 3.13; 4.44] [ 4.11; 5.66] [ 1.80; 4.39] #> 34 D3 [Min;Max] [-0.16;3.90] [ 2.46;6.01] [ 3.16;7.37] [-0.16;7.37] #> 35 D3 Missing 0 1 1 2 #> 36 #> 37 D4 N 30 20 16 66 #> 38 D4 Coef. Var 0.46 0.25 0.20 0.52 #> 39 D4 Mean (SD) 1.83(0.85) 3.80(0.95) 5.17(1.03) 3.22(1.66) #> 40 D4 Median 1.67 3.83 4.88 3.16 #> 41 D4 Mode 2.32 3.50 4.88 2.32 #> 42 D4 [Q1;Q3] [ 1.26; 2.32] [ 3.12; 4.42] [ 4.69; 5.50] [ 1.69; 4.48] #> 43 D4 [Min;Max] [ 0.38;3.97] [ 2.31;5.41] [ 3.24;6.96] [ 0.38;6.96] #> 44 D4 Missing 1 1 1 3 #> 45 #> 46 D5 N 30 20 16 66 #> 47 D5 Coef. Var 0.53 0.33 0.22 0.45 #> 48 D5 Mean (SD) 2.27(1.20) 3.64(1.19) 4.43(0.98) 3.21(1.45) #> 49 D5 Median 2.50 3.86 4.57 3.28 #> 50 D5 Mode 1.87 3.89 2.95 1.87 #> 51 D5 [Q1;Q3] [ 1.77; 3.21] [ 2.59; 4.60] [ 3.44; 4.97] [ 2.42; 4.44] #> 52 D5 [Min;Max] [-1.19;4.31] [ 0.91;5.12] [ 2.95;6.54] [-1.19;6.54] #> 53 D5 Missing 0 0 0 0 #> #> ############################################ #>