title: “Groupe de traitement patients Toulouse” author: “Siham” date: “30/07/2021” output: html_document: toc: yes toc_float: yes pdf_document: toc: yes —

Statistiques descriptives des variables quantitatives

Data

Nous allons ici employer les données description :`

###Comparaison des deux groupes G1 et G2 Toulosue

library(tidyverse)

## Warning: package 'tidyverse' was built under R version 4.0.5

## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --

## v tibble  3.1.3     v dplyr   1.0.7
## v tidyr   1.1.3     v stringr 1.4.0
## v readr   2.0.0     v forcats 0.5.1
## v purrr   0.3.4

## Warning: package 'tibble' was built under R version 4.0.5

## Warning: package 'tidyr' was built under R version 4.0.5

## Warning: package 'readr' was built under R version 4.0.5

## Warning: package 'dplyr' was built under R version 4.0.5

## Warning: package 'forcats' was built under R version 4.0.5

## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter()    masks stats::filter()
## x dplyr::lag()       masks stats::lag()
## x dplyr::recode()    masks car::recode()
## x purrr::some()      masks car::some()
## x dplyr::src()       masks Hmisc::src()
## x dplyr::summarize() masks Hmisc::summarize()

Comparaison sur la base de la VEMS apres traitement

ggplot(toulouse_total, aes(y=VEMS.ml_1, x=Groupe, colour=Groupe, fill=Groupe))+
     geom_jitter(height=0, width=0.25)+
    geom_boxplot(alpha=0.5,notch=TRUE)

## notch went outside hinges. Try setting notch=FALSE.

comparaison sur la base de la repose HID

toulouse_total %>%
 filter(!(Repondeur_HID %in% "")) %>%
 ggplot() +
  aes(x = Repondeur_HID, fill = Groupe) +
  geom_bar() +
  scale_fill_hue(direction = 1) +
  labs(
    x = "Reponse selon HID",
    title = "Comparaison entre les deux groupes "
  ) +
  theme_minimal() +
  theme(plot.title = element_text(hjust = 0.5)) +
  facet_wrap(vars(Groupe))

toulouse_total %>%
 filter(!(Repondeur_VEMS %in% "")) %>%
 ggplot() +
  aes(x = Repondeur_VEMS, fill = Groupe) +
  geom_bar() +
  scale_fill_hue(direction = 1) +
  labs(
    x = "Reponse selon VEMS",
    title = "Comparaison entre les deux groupes "
  ) +
  theme_minimal() +
  theme(plot.title = element_text(hjust = 0.5)) +
  facet_wrap(vars(Groupe))

#test unilateraux

d_donnee <- read.csv2("C:/Users/mallah.s/Desktop/StatsTheses/These_Romane/Av_Ap/d_donnee.csv", stringsAsFactors=TRUE)

##les tests vont se faire à partir des d = donnée au temps T0 -donnée au temps T1 ensuite comparaison des d des deux groupes des patients du centre de toulouse : groupe G1 ( patient 1-15) et le groupe G2 ( la suite des patients)

t.test(d_donnee$volume_lobe_T~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$volume_lobe_T by d_donnee$Groupe
## t = -1.6631, df = 31, p-value = 0.1064
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -949.85851   96.56962
## sample estimates:
## mean in group G1 mean in group G2 
##          865.800         1292.444

t.test(d_donnee$MMRC~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$MMRC by d_donnee$Groupe
## t = -0.51515, df = 31, p-value = 0.6101
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.9507964  0.5673377
## sample estimates:
## mean in group G1 mean in group G2 
##         1.071429         1.263158

t.test(d_donnee$BODE~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$BODE by d_donnee$Groupe
## t = -2.2286, df = 25, p-value = 0.03507
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -3.2470025 -0.1279975
## sample estimates:
## mean in group G1 mean in group G2 
##           1.0000           2.6875

t.test(d_donnee$VEMS~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$VEMS by d_donnee$Groupe
## t = 1.2685, df = 32, p-value = 0.2138
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -59.68087 256.73350
## sample estimates:
## mean in group G1 mean in group G2 
##        -132.0000        -230.5263

t.test(d_donnee$Tiffe~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$Tiffe by d_donnee$Groupe
## t = 0.77378, df = 32, p-value = 0.4447
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -4.024494  8.955161
## sample estimates:
## mean in group G1 mean in group G2 
##         1.865333        -0.600000

t.test(d_donnee$CV_ml~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$CV_ml by d_donnee$Groupe
## t = 0.76831, df = 32, p-value = 0.4479
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -265.8028  587.7536
## sample estimates:
## mean in group G1 mean in group G2 
##        -425.8667        -586.8421

t.test(d_donnee$CVF_ml~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$CVF_ml by d_donnee$Groupe
## t = 1.6582, df = 31, p-value = 0.1074
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -70.65212 685.05814
## sample estimates:
## mean in group G1 mean in group G2 
##        -306.4286        -613.6316

t.test(d_donnee$VR_ml~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$VR_ml by d_donnee$Groupe
## t = -0.90004, df = 32, p-value = 0.3748
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1094.2444   423.5777
## sample estimates:
## mean in group G1 mean in group G2 
##         554.6667         890.0000

t.test(d_donnee$CPT_ml~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$CPT_ml by d_donnee$Groupe
## t = -1.4805, df = 32, p-value = 0.1485
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -749.5880  118.5775
## sample estimates:
## mean in group G1 mean in group G2 
##         165.6000         481.1053

t.test(d_donnee$TLCO~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$TLCO by d_donnee$Groupe
## t = 0.37812, df = 22, p-value = 0.709
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -5.111922  7.391642
## sample estimates:
## mean in group G1 mean in group G2 
##        -1.090909        -2.230769

t.test(d_donnee$Pi_pct~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$Pi_pct by d_donnee$Groupe
## t = -0.74418, df = 12, p-value = 0.4711
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -75.23276  36.92507
## sample estimates:
## mean in group G1 mean in group G2 
##        -44.00000        -24.84615

t.test(d_donnee$Ci_rest_recalc~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$Ci_rest_recalc by d_donnee$Groupe
## t = 0.2912, df = 22, p-value = 0.7736
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -457.0917  606.4250
## sample estimates:
## mean in group G1 mean in group G2 
##        73.333333        -1.333333

t.test(d_donnee$temps_sec~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$temps_sec by d_donnee$Groupe
## t = 1.1724, df = 24, p-value = 0.2525
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -55.52199 201.55835
## sample estimates:
## mean in group G1 mean in group G2 
##        -35.18182       -108.20000

t.test(d_donnee$VO2_max~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$VO2_max by d_donnee$Groupe
## t = 0.23694, df = 15, p-value = 0.8159
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.1322702  0.1653559
## sample estimates:
## mean in group G1 mean in group G2 
##      -0.06285714      -0.07940000

t.test(d_donnee$dist_parc~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$dist_parc by d_donnee$Groupe
## t = 0.87508, df = 25, p-value = 0.3899
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -52.36476 129.73976
## sample estimates:
## mean in group G1 mean in group G2 
##         -13.0000         -51.6875

t.test(d_donnee$Nadir_sat~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$Nadir_sat by d_donnee$Groupe
## t = 1.6629, df = 26, p-value = 0.1083
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -2.715546 25.715546
## sample estimates:
## mean in group G1 mean in group G2 
##              8.5             -3.0

t.test(d_donnee$EELV_repos~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$EELV_repos by d_donnee$Groupe
## t = -1.1693, df = 22, p-value = 0.2548
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1472.0121   410.5455
## sample estimates:
## mean in group G1 mean in group G2 
##        -16.66667        514.06667

t.test(d_donnee$EELV_pic~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$EELV_pic by d_donnee$Groupe
## t = -1.5956, df = 22, p-value = 0.1248
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1204.6901   157.0013
## sample estimates:
## mean in group G1 mean in group G2 
##         215.5556         739.4000

t.test(d_donnee$EELV_isoP~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$EELV_isoP by d_donnee$Groupe
## t = -1.5461, df = 22, p-value = 0.1363
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1381.5517   201.4184
## sample estimates:
## mean in group G1 mean in group G2 
##         223.3333         813.4000

t.test(d_donnee$P_Reponse~ d_donnee$Groupe, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  d_donnee$P_Reponse by d_donnee$Groupe
## t = -0.8304, df = 32, p-value = 0.4125
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.4725102  0.1988260
## sample estimates:
## mean in group G1 mean in group G2 
##        0.6000000        0.7368421