Type: Package
Title: A few Useful Functions for Statisticians
Version: 2.4
Date: 2025-03-24
Maintainer: Hugo Varet <varethugo@gmail.com>
Depends: survival
Imports: stats, graphics, WriteXLS (≥ 2.3.0)
Description: Various useful functions for statisticians: describe data, plot Kaplan-Meier curves with numbers of subjects at risk, compare data sets, display spaghetti-plot, build multi-contingency tables...
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2025-03-24 10:42:54 UTC; hvaret
Author: Hugo Varet [aut, cre]
Repository: CRAN
Date/Publication: 2025-03-24 11:10:02 UTC

A few useful functions for statisticians

Description

Various useful functions for statisticians: describe data, plot Kaplan-Meier curves with numbers of subjects at risk, compare data sets, display spaghetti-plot, build multi-contingency tables...

Author(s)

Hugo Varet

OR and their confidence intervals for logistic regressions

Description

Computes odd ratios and their confidence intervals for logistic regressions

Usage

IC_OR_glm(model, alpha = 0.05)

Arguments

model

a glm object

alpha

type I error, 0.05 by default

Value

A matrix with the estimaed coefficients of the logistic model, their s.e., z-values, p-values, OR and CI of the OR

Author(s)

Hugo Varet

Examples

IC_OR_glm(glm(inherit~sex+age,data=cgd,family="binomial"))

RR and their confidence intervals for Cox models

Description

Computess risk ratios and their confidence intervals for Cox models

Usage

IC_RR_coxph(model, alpha = 0.05, sided = 2)

Arguments

model

a coxph object

alpha

type I error, 0.05 by default

sided

1 or 2 for one or two-sided

Value

A matrix with the estimaed coefficients of the Cox model, their s.e., z-values, p-values, RR and CI of the RR

Author(s)

Hugo Varet

Examples

cgd$time=cgd$tstop-cgd$tstart
IC_RR_coxph(coxph(Surv(time,status)~sex+age,data=cgd),alpha=0.05,sided=1)

Comparing two databases assumed to be identical

Description

Compares two data frames assumed to be identical, prints the differences in the console and also returns the results in a data frame

Usage

compare(d1, d2, id, file.export = NULL)

Arguments

d1

first data frame

d2

second data frame

id

character string, primary key of the two data bases

file.export

character string, name of the XLS file exported

Value

A data frame containing the differences between the two data bases

Author(s)

Hugo Varet

Examples

N=100
data1=data.frame(id=1:N,a=rnorm(N),
                        b=factor(sample(LETTERS[1:5],N,TRUE)),
                        c=as.character(sample(LETTERS[1:5],N,TRUE)),
                        d=as.Date(32768:(32768+N-1),origin="1900-01-01"))
data1$c=as.character(data1$c)
data2=data1
data2$id[3]=4654
data2$a[30]=NA
data2$a[31]=45
data2$b=as.character(data2$b)
data2$d=as.character(data2$d)
data2$e=rnorm(N)
compare(data1,data2,"id")

Convert variables of a data frame in factors

Description

Converts variables of a data frame in factors

Usage

convert_factor(data, vars)

Arguments

data

the data frame in which we can find vars

vars

vector of character string of covariates

Value

The modified data frame

Author(s)

Hugo Varet

Examples

cgd$steroids
cgd$status
cgd=convert_factor(cgd,c("steroids","status"))

Convert 0s in NA

Description

Converts 0s in NA

Usage

convert_zero_NA(data, vars)

Arguments

data

the data frame in which we can find vars

vars

a character vector of covariates for which to transform 0s in NA

Value

The modified data frame

Author(s)

Hugo Varet

Examples

my.data=data.frame(x=rbinom(20,1,0.5),y=rbinom(20,1,0.5),z=rbinom(20,1,0.5))
my.data=convert_zero_NA(my.data,c("y","z"))

Cut a quantitative variable in n equal parts

Description

Cuts a quantitative variable in n equal parts

Usage

cut_quanti(x, n, ...)

Arguments

x

a numeric vector

n

numeric, the number of parts: 2 to cut according to the median, and so on...

...

other arguments to be passed in cut

Value

A factor vector

Author(s)

Hugo Varet

Examples

cut_quanti(cgd$height, 3)

Making descriptive statistics

Description

Makes descriptive statistics of a data frame according to a group covariate or not, can export the results

Usage

desc(
  data,
  vars,
  group = NULL,
  whole = TRUE,
  vars.labels = vars,
  group.labels = NULL,
  type.quanti = "mean",
  test.quanti = "param",
  test = TRUE,
  noquote = TRUE,
  justify = TRUE,
  digits = 2,
  file.export = NULL,
  language = "english"
)

Arguments

data

data frame to describe in which we can find vars and group

vars

vector of character strings of the covariates to describe

group

character string, statistics created for each levels of this covariate

whole

boolean, TRUE to add a column with the whole statistics when comparing groups (set to FALSE if group=NULL)

vars.labels

vector of character string for sweeter names of covariates in the output

group.labels

vector of character string for sweeter column names

type.quanti

character string, "med" to compute median [Q1;Q3], "mean" to compute mean (sd), "mean_med" to compute both mean (sd) and median [Q1;Q3] or "med_mm", "mean_mm" or "mean_med_mm" to add (min;max)

test.quanti

character string, "param" to compute parametric tests for quantitative covariates (t-test or ANOVA) or "nonparam" for non parametric tests (Wilcoxon test or Kruskal-Wallis test)

test

boolean, TRUE to perform tests (FALSE if group is NULL): Khi-2 or Fisher exact test for categorical covariates, t-test/ANOVA or Wilcoxon/Kruskal-Wallis Rank Sum Test for numerical covariates

noquote

boolean, TRUE to hide quotes when printing the table

justify

boolean, TRUE to justify columns on right or left (FALSE if export)

digits

number of digits of the statistics (mean, sd, median, min, max, Q1, Q3, %), p-values always have 3 digits

file.export

character string, name of the XLS file exported

language

character string, "french" or "english"

Value

A matrix of the descriptive statistics

Author(s)

Hugo Varet

Examples

cgd$steroids=factor(cgd$steroids)
cgd$status=factor(cgd$status)
desc(cgd,vars=c("center","sex","age","height","weight","steroids","status"),group="treat")

Plot a histogram with a boxplot below

Description

Plots a histogram with a boxplot below

Usage

hist_boxplot(
  x,
  freq = TRUE,
  density = FALSE,
  main = NULL,
  xlab = NULL,
  ymax = NULL,
  col.hist = "lightblue",
  col.boxplot = "lightblue",
  ...
)

Arguments

x

a numeric vector

freq

boolean, TRUE for frequency or FALSE probability on the y axis

density

boolean, TRUE to plot the estimated density

main

character string, main title of the histogram

xlab

character string, label of the x axis

ymax

numeric value, maximum of the y axis

col.hist

color of the histogram

col.boxplot

color of the boxplot

...

other arguments to be passed in hist()

Value

None

Author(s)

Hugo Varet

Examples

par(mfrow=c(1,2))
hist_boxplot(rnorm(100),col.hist="lightblue",col.boxplot="red",freq=TRUE)
hist_boxplot(rnorm(100),col.hist="lightblue",col.boxplot="red",freq=FALSE,density=TRUE)

Multi cross table

Description

Builds a big cross table between several covariates

Usage

multi.table(data, vars)

Arguments

data

the data frame in which we can find vars

vars

vector of character string of covariates

Value

A matrix containing all the contingency tables between the covariates

Author(s)

Hugo Varet

See Also

plot_multi.table

Examples

multi.table(cgd,c("treat","sex","inherit"))

Kaplan-Meier plot with number of subjects at risk below

Description

Kaplan-Meier plot with number of subjects at risk below

Usage

plot_km(
  formula,
  data,
  test = TRUE,
  xy.pvalue = NULL,
  conf.int = FALSE,
  times.print = NULL,
  nrisk.labels = NULL,
  legend = NULL,
  xlab = NULL,
  ylab = NULL,
  ylim = c(0, 1.02),
  left = 4.5,
  bottom = 5,
  cex.mtext = par("cex"),
  lwd = 2,
  lty = 1,
  col = NULL,
  ...
)

Arguments

formula

same formula than in survfit (Surv(time,cens)~group or Surv(time,cens)~1), where cens must equal to 0 (censorship) or 1 (failure)

data

data frame with time, cens and group

test

boolean, TRUE to compute and display the p-value of the log-rank test

xy.pvalue

numeric vector of length 2, coordinates where to display the p-value of the log-rank test

conf.int

boolean, TRUE to display the confidence interval of the curve(s)

times.print

numeric vector, times at which to display the numbers of subjects at risk

nrisk.labels

character vector to modify the levels of group in the table below the curve(s)

legend

character string ("bottomright" for example) or numeric vector (c(x,y)), where to place the legend of the curve(s)

xlab

character string, label of the time axis

ylab

character string, label of the y axis

ylim

numeric vector of length 2, minimum and maximum of the y-axis

left

integer, size of left margin

bottom

integer, number of lines in addition of the table below the graph

cex.mtext

numeric, size of the numbers of subjects at risk

lwd

width of the Kaplan-Meier curve(s)

lty

type of the Kaplan-Meier curve(s)

col

color(s) of the Kaplan-Meier curve(s)

...

other arguments to be passed in plot.survfit

Value

None

Author(s)

Hugo Varet

Examples

cgd$time=cgd$tstop-cgd$tstart
plot_km(Surv(time,status)~sex,data=cgd,col=c("blue","red"))

Spaghetti plot and plot of the mean at each time

Description

Spaghetti plot and plot of the mean at each time

Usage

plot_mm(
  formula,
  data,
  col.spag = 1,
  col.mean = 1,
  type = "spaghettis",
  tick.times = TRUE,
  xlab = NULL,
  ylab = NULL,
  main = "",
  lwd.spag = 1,
  lwd.mean = 4,
  ...
)

Arguments

formula

obs~time+(group|id) or obs~time+(1|id)

data

data frame in which we can find obs, time, group and id

col.spag

vector of length nrow(data) with colors (one for each individual)

col.mean

vector of length length(levels(group)) with colors (one for each group)

type

"spaghettis", "mean" or "both"

tick.times

boolean, TRUE to display ticks at each observation time on the x-axis

xlab

character sring, label of the time axis

ylab

character string, label of the y axis

main

character string, main title

lwd.spag

numeric, width of the spaghetti lines, 1 by default

lwd.mean

numeric, width of the mean lines, 4 by default

...

Other arguments to be passed in plot

Value

None

Author(s)

Hugo Varet on Anais Charles-Nelson's idea

Examples

N=10
time=rep(1:4,N)
obs=1.1*time + rep(0:1,each=2*N) + rnorm(4*N)
my.data=data.frame(id=rep(1:N,each=4),time,obs,group=rep(1:2,each=N*2))
par(xaxs="i",yaxs="i")
plot_mm(obs~time+(group|id),my.data,col.spag=my.data$group,
        col.mean=c("blue","red"),type="both",main="Test plot_mm")

Plot a multi cross table

Description

Plots a multi cross table on a graph

Usage

plot_multi.table(data, vars, main = "")

Arguments

data

the data frame in which we can find vars

vars

vector of character string of covariates

main

main title of the plot

Value

None

Author(s)

Hugo Varet

See Also

multi.table

Examples

plot_multi.table(cgd,c("treat","sex","inherit"))

Plot points with the corresponding linear regression line

Description

Plots points with the corresponding linear regression line

Usage

plot_reg(x, y, pch = 19, xlab = NULL, ylab = NULL, ...)

Arguments

x

numeric vector

y

numeric vector

pch

type of points

xlab

character string, label of the x axis, NULL by default

ylab

character string, label of the y axis, NULL by default

...

other arguments to be passed in plot

Value

None

Author(s)

Hugo Varet

Examples

plot_reg(cgd$age, cgd$height, xlab="Age (years)", ylab="Height")