comparaison_reponse HID VS VEMS

##Comparaison des groupes de rÃ©pondeurs VS non rÃ©pondeurs selon VEMS et selon HID

Schema de Comparaison sur la base de la réponse VEMS des patients HID

ggplot(HID, aes(y=VEMS_ml, x=Repondeur_VEMS, colour=Repondeur_VEMS, fill=Repondeur_VEMS))+
   geom_jitter(height=0, width=0.25)+
   geom_boxplot(alpha=0.5,notch=TRUE)

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

Schema de Comparaison sur la base de la réponse VEMS des patients HID

ggplot(HID, aes(y=VEMS_ml, x=Repondeur_HID, colour=Repondeur_HID, fill=Repondeur_HID))+
      geom_jitter(height=0, width=0.25)+
     geom_boxplot(alpha=0.5,notch=TRUE)

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

#les tests vont se faire à partir de “d” des données (d= donnée T0-donnée T1) des patients ayant une hyperinflation ensuite comparaison des deux groupes des patients selon la reponse : RÃ©pondeur VEMS et rÃ©pondeur HID

Comparaison des groupes Repondeurs/Non repondeurs selon HID

“Volume lobe _ répondeur HID/VEMS”

t.test(HID$volume.lobe~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$volume.lobe by HID$Repondeur_HID
## t = -3.0476, df = 31, p-value = 0.004686
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1147.358  -227.364
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    515.2105                   1202.5714

t.test(HID$volume.lobe~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$volume.lobe by HID$Repondeur_VEMS
## t = -3.9108, df = 31, p-value = 0.0004678
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1242.6513  -390.7932
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    361.3333                   1178.0556

“MMRC _ répondeur HID/VEMS”

t.test(HID$MMRC~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$MMRC by HID$Repondeur_HID
## t = -1.3279, df = 33, p-value = 0.1933
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1.1916014  0.2504249
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    1.000000                    1.470588

t.test(HID$MMRC~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$MMRC by HID$Repondeur_VEMS
## t = -1.1778, df = 33, p-value = 0.2473
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1.1483785  0.3062732
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    1.000000                    1.421053

“BODE _ répondeur HID/VEMS”

t.test(HID$BODE~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$BODE by HID$Repondeur_HID
## t = -3.9336, df = 29, p-value = 0.000479
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -3.179214 -1.004119
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                   0.5333333                   2.6250000

t.test(HID$BODE~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$BODE by HID$Repondeur_VEMS
## t = -2.2603, df = 29, p-value = 0.03149
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -2.6251904 -0.1311121
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                   0.8571429                   2.2352941

“VEMS _ répondeur HID/VEMS”

t.test(HID$VEMS_ml~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$VEMS_ml by HID$Repondeur_HID
## t = 1.7498, df = 35, p-value = 0.08891
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -21.41547 288.82724
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                   -101.0000                   -234.7059

t.test(HID$VEMS_ml~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$VEMS_ml by HID$Repondeur_VEMS
## t = 7.1177, df = 35, p-value = 2.695e-08
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  259.1283 465.9306
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    33.52941                  -329.00000

“Tiffeneau _ répondeur HID/VEMS”

t.test(HID$Tiffe~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$Tiffe by HID$Repondeur_HID
## t = 0.65194, df = 35, p-value = 0.5187
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -3.761594  7.320417
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    0.250000                   -1.529412

t.test(HID$Tiffe~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$Tiffe by HID$Repondeur_VEMS
## t = 2.7354, df = 35, p-value = 0.009716
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##   1.757765 11.877529
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    3.117647                   -3.700000

“CV (ml) _ répondeur HID/VEMS”

t.test(HID$CV_ml~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$CV_ml by HID$Repondeur_HID
## t = 1.3832, df = 35, p-value = 0.1754
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -105.2396  555.2396
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                        -125                        -350

t.test(HID$CV_ml~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$CV_ml by HID$Repondeur_VEMS
## t = 3.0322, df = 35, p-value = 0.00455
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  148.9824 752.6058
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    15.29412                  -435.50000

“CVF(ml) _ répondeur HID/VEMS”

t.test(HID$CVF_ml~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$CVF_ml by HID$Repondeur_HID
## t = 2.5775, df = 35, p-value = 0.01432
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##   80.40666 676.81098
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                   -128.4500                   -507.0588

t.test(HID$CVF_ml~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$CVF_ml by HID$Repondeur_VEMS
## t = 2.677, df = 35, p-value = 0.01123
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##   94.42501 687.12205
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                   -91.17647                  -481.95000

“VR (ml) _ répondeur HID/VEMS”

t.test(HID$VR_ml~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$VR_ml by HID$Repondeur_HID
## t = -1.4826, df = 35, p-value = 0.1471
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -942.7066  146.9419
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    418.0000                    815.8824

t.test(HID$VR_ml~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$VR_ml by HID$Repondeur_VEMS
## t = -3.2278, df = 35, p-value = 0.002709
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1277.0014  -290.8809
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    177.0588                    961.0000

“CPT (ml) _ répondeur HID/VEMS”

t.test(HID$CPT_ml~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$CPT_ml by HID$Repondeur_HID
## t = 0.41515, df = 35, p-value = 0.6806
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -553.7292  838.4174
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    577.0500                    434.7059

t.test(HID$CPT_ml~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$CPT_ml by HID$Repondeur_VEMS
## t = -0.35429, df = 35, p-value = 0.7252
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -818.0959  574.9783
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    445.9412                    567.5000

“TLCO _ répondeur HID/VEMS”

t.test(HID$TLCO~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$TLCO by HID$Repondeur_HID
## t = -1.735, df = 23, p-value = 0.09612
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -10.6242099   0.9319022
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                  -5.0000000                  -0.1538462

t.test(HID$TLCO~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$TLCO by HID$Repondeur_VEMS
## t = -0.038187, df = 23, p-value = 0.9699
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -6.513308  6.277197
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                   -2.555556                   -2.437500

“Pi% _ répondeur HID/VEMS”

t.test(HID$Pi_pct~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$Pi_pct by HID$Repondeur_HID
## t = 0.5246, df = 16, p-value = 0.6071
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -20.14157  33.38833
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                   -27.28571                   -33.90909

t.test(HID$Pi_pct~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$Pi_pct by HID$Repondeur_VEMS
## t = 0.030019, df = 16, p-value = 0.9764
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -26.10743  26.85743
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                     -31.125                     -31.500

“Ci_rest recalculé _ répondeur HID/VEMS”

t.test(HID$Ci_rest.recalc~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$Ci_rest.recalc by HID$Repondeur_HID
## t = 1.417, df = 35, p-value = 0.1653
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -98.50862 553.80274
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    120.0000                   -107.6471

t.test(HID$Ci_rest.recalc~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$Ci_rest.recalc by HID$Repondeur_VEMS
## t = 1.3572, df = 35, p-value = 0.1834
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -108.3598  545.4186
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    133.5294                    -85.0000

“Ci pic recalculé _ répondeur HID/VEMS”

t.test(HID$CI_pic.recalc_2~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$CI_pic.recalc_2 by HID$Repondeur_HID
## t = 4.4845, df = 35, p-value = 7.53e-05
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  214.3649 568.9880
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                     30.5000                   -361.1765

t.test(HID$Ci_rest.recalc~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$Ci_rest.recalc by HID$Repondeur_VEMS
## t = 1.3572, df = 35, p-value = 0.1834
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -108.3598  545.4186
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    133.5294                    -85.0000

“CI_diff_recalculé _ répondeur HID/VEMS”

t.test(HID$CI_diff.recalc~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$CI_diff.recalc by HID$Repondeur_HID
## t = 1.0305, df = 35, p-value = 0.3099
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -159.1182  487.1770
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    -89.5000                   -253.5294

t.test(HID$CI_diff.recalc~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$CI_diff.recalc by HID$Repondeur_VEMS
## t = -0.34902, df = 35, p-value = 0.7292
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -383.7378  271.1496
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                   -195.2941                   -139.0000

“CI Isopuissance _ répondeur HID/VEMS”

t.test(HID$CI_isoP~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$CI_isoP by HID$Repondeur_HID
## t = 7.2684, df = 35, p-value = 1.726e-08
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  481.3824 854.4999
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    105.0000                   -562.9412

t.test(HID$CI_isoP~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$CI_isoP by HID$Repondeur_VEMS
## t = 3.2519, df = 35, p-value = 0.002539
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  155.8677 673.8382
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    22.35294                  -392.50000

“temps en seconde _ répondeur HID/VEMS”

t.test(HID$temps_sec~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$temps_sec by HID$Repondeur_HID
## t = 1.3875, df = 35, p-value = 0.1741
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -34.10065 181.34771
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    15.80000                   -57.82353

t.test(HID$temps_sec~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$temps_sec by HID$Repondeur_VEMS
## t = 0.99714, df = 35, p-value = 0.3255
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -55.51694 162.69929
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    10.94118                   -42.65000

“VT isotime _ répondeur HID/VEMS”

t.test(HID$VT_isotime~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$VT_isotime by HID$Repondeur_HID
## t = 4.5867, df = 35, p-value = 5.553e-05
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  211.6342 547.7423
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                     17.1000                   -362.5882

t.test(HID$VT_isotime~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$VT_isotime by HID$Repondeur_VEMS
## t = 2.9994, df = 35, p-value = 0.004957
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##   90.5559 469.8794
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                   -5.882353                 -286.100000

“VT_pic _ répondeur HID/VEMS”

t.test(HID$vt_pic~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$vt_pic by HID$Repondeur_HID
## t = 3.7586, df = 35, p-value = 0.0006238
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  120.2136 402.5923
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                     29.0500                   -232.3529

t.test(HID$vt_pic~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$vt_pic by HID$Repondeur_VEMS
## t = 2.316, df = 35, p-value = 0.02654
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##   21.93627 333.46373
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                         5.0                      -172.7

“VRI_isotime _ répondeur HID/VEMS”

t.test(HID$VRI_isotime~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$VRI_isotime by HID$Repondeur_HID
## t = 3.5549, df = 35, p-value = 0.001107
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  123.6390 452.8669
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                     87.9000                   -200.3529

t.test(HID$VRI_isotime~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$VRI_isotime by HID$Repondeur_VEMS
## t = 1.4663, df = 35, p-value = 0.1515
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -51.77101 321.04160
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    28.23529                  -106.40000

“distance parcourue _ répondeur HID/VEMS”

t.test(HID$dist_parc~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$dist_parc by HID$Repondeur_HID
## t = 0.62848, df = 30, p-value = 0.5344
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -31.10546  58.76036
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                   -29.70588                   -43.53333

t.test(HID$dist_parc~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$dist_parc by HID$Repondeur_VEMS
## t = 0.56863, df = 30, p-value = 0.5738
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -32.46047  57.51145
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                   -29.53333                   -42.05882

“Nadir _ répondeur HID/VEMS”

t.test(HID$Nadir_sat~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$Nadir_sat by HID$Repondeur_HID
## t = 1.4334, df = 30, p-value = 0.1621
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1.314341  7.502576
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                   0.2941176                  -2.8000000

t.test(HID$Nadir_sat~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$Nadir_sat by HID$Repondeur_VEMS
## t = -0.50064, df = 30, p-value = 0.6203
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -5.683981  3.445886
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                  -1.7857143                  -0.6666667

“EELV au repos _ répondeur HID/VEMS”

t.test(HID$EELV_repos~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$EELV_repos by HID$Repondeur_HID
## t = -0.20649, df = 35, p-value = 0.8376
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -923.9499  753.3440
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    457.0500                    542.3529

t.test(HID$EELV_repos~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$EELV_repos by HID$Repondeur_VEMS
## t = -0.83082, df = 35, p-value = 0.4117
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1171.0914   490.9149
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    312.4118                    652.5000

“EELV pic _ répondeur HID/VEMS”

t.test(HID$EELV_pic~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$EELV_pic by HID$Repondeur_HID
## t = -0.69367, df = 35, p-value = 0.4925
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -979.0358  480.3711
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    546.5500                    795.8824

t.test(HID$EELV_pic~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$EELV_pic by HID$Repondeur_VEMS
## t = -0.79115, df = 35, p-value = 0.4342
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1012.0137   444.4255
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    507.7059                    791.5000

“EELV_IsoP _ répondeur HID/VEMS”

t.test(HID$EELV_isoP~ HID$Repondeur_HID, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$EELV_isoP by HID$Repondeur_HID
## t = -1.4332, df = 35, p-value = 0.1607
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1270.1228   218.9287
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    472.0500                    997.6471

t.test(HID$EELV_isoP~ HID$Repondeur_VEMS, var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  HID$EELV_isoP by HID$Repondeur_VEMS
## t = -1.4644, df = 35, p-value = 0.152
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1280.0287   207.2052
## sample estimates:
## mean in group Non répondeur     mean in group Répondeur 
##                    423.5882                    960.0000