#Carregar bibliotecas necessárias
#Carregar bibliotecas necessárias
library(dplyr)
library(ggplot2)
library(multcomp)
library(car)
library(lmtest)
library(plotly)
library(tibble)
library("bestglm")
library("ggplot2")
library(visdat)
library(regclass)
library(ExpDes.pt)
library(agricolae)
library(gridExtra)
library(grid)
library(xfun)
library(knitr)
library(knitrdata)
library(car)
library(patchwork)
library(multcomp)
title: “Covid_Longa”
author: ” Maria Thereza,Camila , Marcelo Ribeiro, Frank - Lafex ”
date: “2025-02-17”
format: html
Carregar os dados
Classificar natureza das variáveis
'data.frame': 40 obs. of 29 variables:
$ numero_da_amostra: chr "1" "2" "3" "4" ...
$ nome : chr "Angelita Trindade dos Santos" "Anilson Junior da Silva de Campos" "Wandiclecia Rodrigues Ferreirea" "Maria Efigenia Bernarda Soares" ...
$ Sexo : Factor w/ 2 levels "fem","masc": 1 2 1 1 2 1 2 1 1 1 ...
$ Classificação : Factor w/ 2 levels "Nao_obeso","obeso": 2 1 1 1 2 1 2 2 2 2 ...
$ Risco_Pesc : Factor w/ 2 levels "Normal","Risco elevado": 2 2 1 1 2 1 2 2 2 2 ...
$ Risco_cardio : Factor w/ 3 levels "Alto","Baixo",..: 1 1 1 1 1 2 1 2 1 3 ...
$ tempo_Covid : num 3 3.5 2 1.5 2.5 4 3.5 3 2 2 ...
$ N_Covid : int 2 1 1 1 1 3 1 2 1 2 ...
$ Sintomas : Factor w/ 2 levels "Não","Sim": 2 2 1 1 1 2 2 2 2 1 ...
$ HbGlic : num 5.3 5.3 5.1 8.3 5.4 5.8 4.9 5.8 5.6 5.4 ...
$ ClasseGlicada : Factor w/ 3 levels "Diabetes","Normal",..: 2 2 2 1 2 3 2 3 2 2 ...
$ VitD : num 26 30 23 16 29 21 21 26 27 14 ...
$ ClasseVitD : Factor w/ 2 levels "Baixa","Normal": 1 2 1 1 1 1 1 1 1 1 ...
$ Trig : num 118 180 91 426 153 134 187 96 91 172 ...
$ Class_Trig : Factor w/ 2 levels "Alto","Baixo": 2 1 2 1 1 2 1 2 2 1 ...
$ CH50 : num 79.3 45 60.4 96 66.4 ...
$ Classe_CH50 : Factor w/ 3 levels "Alto","Baixo",..: 3 3 3 1 3 1 3 3 3 3 ...
$ SOD.mg_ptn : num 1 2.026 1.39 1.476 0.802 ...
$ CAT : num 0.596 1.014 0.976 0.515 0.521 ...
$ TBARs : num 0.0448 0.1774 0.1328 0.1132 0.0982 ...
$ PTN_CARB : num 2.24 3.27 2.15 2.29 2.67 ...
$ FEV1.pred : num 93 85 110 94 74 97 76 75 72 83 ...
$ Classe_Fev1_pre : Factor w/ 4 levels "Leve","Moderado",..: 3 3 3 3 1 3 1 1 1 3 ...
$ predFEV1post : num 96 78 113 94 83 100 76 82 83 82 ...
$ Classe_Fev1_pós : Factor w/ 4 levels "Leve","Moderada",..: 3 1 3 3 3 3 1 3 3 3 ...
$ IL_10 : num 2375 2888 2829 2961 2580 ...
$ Lep : num 2084 2636 2066 2458 2111 ...
$ TNF : num 2754 3672 3870 3006 3204 ...
$ IL_17A : num 1064 1094 856 1043 846 ...
Pressupostos
Normalidade
variavel p_value normalidade
1 tempo_Covid 3.630395e-02 Não Normal
2 HbGlic 1.319530e-08 Não Normal
3 VitD 2.111857e-03 Não Normal
4 Trig 1.032014e-04 Não Normal
5 CH50 2.181509e-03 Não Normal
6 SOD.mg_ptn 1.630162e-02 Não Normal
7 CAT 2.709300e-11 Não Normal
8 TBARs 1.241179e-06 Não Normal
9 PTN_CARB 8.031895e-01 Normal
10 FEV1.pred 4.287182e-02 Não Normal
11 predFEV1post 5.402040e-02 Normal
12 IL_10 3.025229e-05 Não Normal
13 Lep 5.402827e-03 Não Normal
14 TNF 5.959556e-08 Não Normal
15 IL_17A 4.513822e-03 Não Normal
Desbalanceamento de classes
Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
ℹ Please use tidy evaluation idioms with `aes()`.
ℹ See also `vignette("ggplot2-in-packages")` for more information.
Variável : Risco Pescoço
##Testes - Risco Pescoço vs Variáveis numéricas
[1] "Normal" "Risco elevado"
0 1
12 28
Variavel Estatistica P_valor
W tempo_Covid 115.5 0.11914458
W1 HbGlic 110.0 0.08858686
W2 VitD 140.5 0.42250178
W3 Trig 86.0 0.01600061
W4 CH50 184.0 0.64615693
W5 SOD.mg_ptn 164.0 0.26301057
W6 CAT 125.0 0.81731496
W7 TBARs 124.5 0.80353946
W8 PTN_CARB 110.0 0.67598786
W9 FEV1.pred 132.0 0.50191621
W10 predFEV1post 129.5 0.45347603
W11 IL_10 113.5 0.41943794
W12 Lep 92.5 0.12633801
W13 TNF 121.5 0.59440073
W14 IL_17A 85.5 0.07667488
Boxplots - Risco Pescoço vs Variáveis numéricas
Medidas descritivas - Risco Pescoço
Attaching package: 'kableExtra'
The following object is masked from 'package:dplyr':
group_rows
Risco_Pesc | HbGlic_Media | HbGlic_Mediana | HbGlic_IQR | HbGlic_Desvio_Padrao | HbGlic_Variancia | VitD_Media | VitD_Mediana | VitD_IQR | VitD_Desvio_Padrao | VitD_Variancia | Trig_Media | Trig_Mediana | Trig_IQR | Trig_Desvio_Padrao | Trig_Variancia | CH50_Media | CH50_Mediana | CH50_IQR | CH50_Desvio_Padrao | CH50_Variancia | SOD.mg_ptn_Media | SOD.mg_ptn_Mediana | SOD.mg_ptn_IQR | SOD.mg_ptn_Desvio_Padrao | SOD.mg_ptn_Variancia | CAT_Media | CAT_Mediana | CAT_IQR | CAT_Desvio_Padrao | CAT_Variancia | TBARs_Media | TBARs_Mediana | TBARs_IQR | TBARs_Desvio_Padrao | TBARs_Variancia | PTN_CARB_Media | PTN_CARB_Mediana | PTN_CARB_IQR | PTN_CARB_Desvio_Padrao | PTN_CARB_Variancia | FEV1.pred_Media | FEV1.pred_Mediana | FEV1.pred_IQR | FEV1.pred_Desvio_Padrao | FEV1.pred_Variancia | predFEV1post_Media | predFEV1post_Mediana | predFEV1post_IQR | predFEV1post_Desvio_Padrao | predFEV1post_Variancia | IL_10_Media | IL_10_Mediana | IL_10_IQR | IL_10_Desvio_Padrao | IL_10_Variancia | Lep_Media | Lep_Mediana | Lep_IQR | Lep_Desvio_Padrao | Lep_Variancia | TNF_Media | TNF_Mediana | TNF_IQR | TNF_Desvio_Padrao | TNF_Variancia | IL_17A_Media | IL_17A_Mediana | IL_17A_IQR | IL_17A_Desvio_Padrao | IL_17A_Variancia | tempo_Covid_Media | tempo_Covid_Mediana | tempo_Covid_IQR | tempo_Covid_Desvio_Padrao | tempo_Covid_Variancia |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Normal | 5.258333 | 5.05 | 0.400 | 1.042251 | 1.086288 | 29.00000 | 25 | 8.5 | 12.150571 | 147.63636 | 132.1667 | 91 | 68.00 | 110.07339 | 12116.152 | 70.72167 | 65.725 | 42.9175 | 21.83316 | 476.6867 | 1.0206091 | 0.98730 | 0.465000 | 0.3426179 | 0.1173870 | 0.9897727 | 0.97580 | 0.502850 | 0.4133759 | 0.1708796 | 0.1045182 | 0.09090 | 0.0416 | 0.0726867 | 0.0052834 | 2.45200 | 2.3583 | 0.707000 | 0.5042916 | 0.2543101 | 83.00000 | 84.0 | 15.0 | 18.29754 | 334.8000 | 84.00 | 88 | 13.00 | 19.44222 | 378.0000 | 2745.427 | 2756.1 | 234.55 | 167.8017 | 28157.42 | 2081.750 | 1995.1 | 360.7255 | 275.3647 | 75825.70 | 3362.854 | 3060.115 | 324.012 | 766.7028 | 587833.2 | 971.0037 | 931.869 | 119.0165 | 158.3352 | 25070.03 | 2.125000 | 2.0 | 0.7 | 0.9928151 | 0.9856818 |
Risco elevado | 5.707143 | 5.50 | 0.775 | 1.494416 | 2.233280 | 28.14286 | 30 | 4.5 | 5.448169 | 29.68254 | 173.2857 | 143 | 61.25 | 82.97651 | 6885.101 | 68.34536 | 70.545 | 35.5425 | 19.09227 | 364.5148 | 0.9476458 | 0.84985 | 0.242625 | 0.3296843 | 0.1086918 | 1.4912333 | 1.02665 | 0.564925 | 2.2789748 | 5.1937263 | 0.1140625 | 0.09135 | 0.0481 | 0.0816490 | 0.0066666 | 2.37699 | 2.2860 | 0.821125 | 0.7486220 | 0.5604348 | 88.85714 | 86.5 | 18.5 | 11.33240 | 128.4233 | 90.75 | 89 | 14.25 | 11.47501 | 131.6759 | 2914.412 | 2785.4 | 425.10 | 441.9718 | 195339.05 | 2212.068 | 2146.5 | 320.7000 | 314.0308 | 98615.36 | 3433.809 | 3204.121 | 522.020 | 871.5823 | 759655.7 | 1036.8056 | 1002.772 | 146.8700 | 143.8082 | 20680.79 | 2.540357 | 2.5 | 1.0 | 0.8494725 | 0.7216036 |
Variável : Obesidade
Testes - Obesidade vs Variáveis numéricas
[1] "Nao_obeso" "obeso"
0 1
25 15
Variavel Estatistica P_valor
W tempo_Covid 170.0 0.629629087
W1 HbGlic 77.0 0.002044643
W2 VitD 191.0 0.932770642
W3 Trig 139.5 0.183864034
W4 CH50 128.0 0.098086308
W5 SOD.mg_ptn 187.0 0.137526470
W6 CAT 141.5 0.972762147
W7 TBARs 166.5 0.432267702
W8 PTN_CARB 145.0 0.085167609
W9 FEV1.pred 191.0 0.761643055
W10 predFEV1post 148.5 0.370456601
W11 IL_10 182.5 0.284231777
W12 Lep 83.0 0.029675693
W13 TNF 153.0 0.921268477
W14 IL_17A 130.0 0.531075661
Boxplots - Obesidade
Medidas descritivas - Obesidade
Classificação | HbGlic_Media | HbGlic_Mediana | HbGlic_IQR | HbGlic_Desvio_Padrao | HbGlic_Variancia | VitD_Media | VitD_Mediana | VitD_IQR | VitD_Desvio_Padrao | VitD_Variancia | Trig_Media | Trig_Mediana | Trig_IQR | Trig_Desvio_Padrao | Trig_Variancia | CH50_Media | CH50_Mediana | CH50_IQR | CH50_Desvio_Padrao | CH50_Variancia | SOD.mg_ptn_Media | SOD.mg_ptn_Mediana | SOD.mg_ptn_IQR | SOD.mg_ptn_Desvio_Padrao | SOD.mg_ptn_Variancia | CAT_Media | CAT_Mediana | CAT_IQR | CAT_Desvio_Padrao | CAT_Variancia | TBARs_Media | TBARs_Mediana | TBARs_IQR | TBARs_Desvio_Padrao | TBARs_Variancia | PTN_CARB_Media | PTN_CARB_Mediana | PTN_CARB_IQR | PTN_CARB_Desvio_Padrao | PTN_CARB_Variancia | FEV1.pred_Media | FEV1.pred_Mediana | FEV1.pred_IQR | FEV1.pred_Desvio_Padrao | FEV1.pred_Variancia | predFEV1post_Media | predFEV1post_Mediana | predFEV1post_IQR | predFEV1post_Desvio_Padrao | predFEV1post_Variancia | IL_10_Media | IL_10_Mediana | IL_10_IQR | IL_10_Desvio_Padrao | IL_10_Variancia | Lep_Media | Lep_Mediana | Lep_IQR | Lep_Desvio_Padrao | Lep_Variancia | TNF_Media | TNF_Mediana | TNF_IQR | TNF_Desvio_Padrao | TNF_Variancia | IL_17A_Media | IL_17A_Mediana | IL_17A_IQR | IL_17A_Desvio_Padrao | IL_17A_Variancia | tempo_Covid_Media | tempo_Covid_Mediana | tempo_Covid_IQR | tempo_Covid_Desvio_Padrao | tempo_Covid_Variancia |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Nao_obeso | 5.184 | 5.1 | 0.70 | 0.7904007 | 0.6247333 | 28.96000 | 29 | 7.0 | 8.927859 | 79.70667 | 152.7200 | 140 | 83.0 | 94.71119 | 8970.210 | 65.15160 | 61.67 | 28.140 | 19.44811 | 378.2288 | 1.0442045 | 0.97545 | 0.48945 | 0.3792959 | 0.1438654 | 1.021918 | 0.99505 | 0.625475 | 0.409231 | 0.167470 | 0.1241136 | 0.0925 | 0.057875 | 0.0921221 | 0.0084865 | 2.594132 | 2.4199 | 0.85405 | 0.6444889 | 0.4153660 | 87.04167 | 85.5 | 16.5 | 15.07511 | 227.2591 | 86.83333 | 88.5 | 12.25 | 16.02625 | 256.8406 | 2880.374 | 2829.4 | 439.8 | 301.8912 | 91138.29 | 2092.298 | 2021.8 | 311.7 | 250.7580 | 62879.56 | 3514.828 | 3132.118 | 612.023 | 1006.1692 | 1012376.5 | 1012.901 | 947.063 | 202.5805 | 162.0642 | 26264.81 | 2.373200 | 2.0 | 1.5 | 1.0189239 | 1.0382060 |
obeso | 6.220 | 5.8 | 0.65 | 1.8686129 | 3.4917143 | 27.46667 | 29 | 6.5 | 5.962582 | 35.55238 | 174.6667 | 149 | 69.5 | 90.07034 | 8112.667 | 75.56933 | 79.34 | 33.745 | 18.96978 | 359.8525 | 0.8459769 | 0.83620 | 0.23300 | 0.1759907 | 0.0309727 | 1.861146 | 1.03900 | 0.576800 | 3.079356 | 9.482434 | 0.0889769 | 0.0886 | 0.047500 | 0.0393141 | 0.0015456 | 2.070118 | 1.9553 | 0.81140 | 0.5987485 | 0.3584997 | 87.46667 | 87.0 | 19.0 | 11.51934 | 132.6952 | 92.06667 | 94.0 | 15.50 | 10.47082 | 109.6381 | 2831.646 | 2682.8 | 234.5 | 513.4104 | 263590.28 | 2313.700 | 2146.5 | 400.8 | 349.3179 | 122022.97 | 3230.429 | 3204.121 | 162.007 | 316.8166 | 100372.7 | 1023.420 | 997.708 | 75.9680 | 129.5409 | 16780.83 | 2.486667 | 2.5 | 1.0 | 0.6937133 | 0.4812381 |
Variável: Sintomas
Testes- Sintomas vs Variáveis numéricas
[1] "Não" "Sim"
0 1
16 24
Variavel Estatistica P_valor
W tempo_Covid 169.5 0.5374128
W1 HbGlic 193.0 0.9889485
W2 VitD 199.5 0.8457700
W3 Trig 205.5 0.7192768
W4 CH50 216.0 0.5149752
W5 SOD.mg_ptn 138.0 0.8779035
W6 CAT 129.5 0.6571331
W7 TBARs 161.5 0.5388216
W8 PTN_CARB 101.0 0.7831880
W9 FEV1.pred 208.0 0.5019351
W10 predFEV1post 212.0 0.4319748
W11 IL_10 157.5 0.8048139
W12 Lep 190.0 0.1875661
W13 TNF 146.5 0.9343578
W14 IL_17A 101.5 0.1173692
Boxplots - Sintomas vs Variáveis numéricas
Medidas descritivas - Sintomas
Sintomas | HbGlic_Media | HbGlic_Mediana | HbGlic_IQR | HbGlic_Desvio_Padrao | HbGlic_Variancia | VitD_Media | VitD_Mediana | VitD_IQR | VitD_Desvio_Padrao | VitD_Variancia | Trig_Media | Trig_Mediana | Trig_IQR | Trig_Desvio_Padrao | Trig_Variancia | CH50_Media | CH50_Mediana | CH50_IQR | CH50_Desvio_Padrao | CH50_Variancia | SOD.mg_ptn_Media | SOD.mg_ptn_Mediana | SOD.mg_ptn_IQR | SOD.mg_ptn_Desvio_Padrao | SOD.mg_ptn_Variancia | CAT_Media | CAT_Mediana | CAT_IQR | CAT_Desvio_Padrao | CAT_Variancia | TBARs_Media | TBARs_Mediana | TBARs_IQR | TBARs_Desvio_Padrao | TBARs_Variancia | PTN_CARB_Media | PTN_CARB_Mediana | PTN_CARB_IQR | PTN_CARB_Desvio_Padrao | PTN_CARB_Variancia | FEV1.pred_Media | FEV1.pred_Mediana | FEV1.pred_IQR | FEV1.pred_Desvio_Padrao | FEV1.pred_Variancia | predFEV1post_Media | predFEV1post_Mediana | predFEV1post_IQR | predFEV1post_Desvio_Padrao | predFEV1post_Variancia | IL_10_Media | IL_10_Mediana | IL_10_IQR | IL_10_Desvio_Padrao | IL_10_Variancia | Lep_Media | Lep_Mediana | Lep_IQR | Lep_Desvio_Padrao | Lep_Variancia | TNF_Media | TNF_Mediana | TNF_IQR | TNF_Desvio_Padrao | TNF_Variancia | IL_17A_Media | IL_17A_Mediana | IL_17A_IQR | IL_17A_Desvio_Padrao | IL_17A_Variancia | tempo_Covid_Media | tempo_Covid_Mediana | tempo_Covid_IQR | tempo_Covid_Desvio_Padrao | tempo_Covid_Variancia |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Não | 5.9250 | 5.3 | 1.200 | 2.0667204 | 4.2713333 | 27.56250 | 30.0 | 8.0 | 6.521439 | 42.52917 | 157.5625 | 143.5 | 88.25 | 89.33605 | 7980.929 | 72.09562 | 73.290 | 34.675 | 20.32270 | 413.0123 | 0.9797769 | 0.8507 | 0.58450 | 0.3265416 | 0.1066294 | 1.046623 | 0.9286 | 0.383400 | 0.5139705 | 0.2641656 | 0.1052154 | 0.1032 | 0.0407 | 0.0485290 | 0.0023551 | 2.318658 | 2.31135 | 0.701550 | 0.4995985 | 0.2495986 | 90.00000 | 85.5 | 14.5 | 12.52198 | 156.8000 | 92.00000 | 89.5 | 12.25 | 13.2916 | 176.6667 | 2918.485 | 2829.4 | 307.8 | 504.8430 | 254866.42 | 2295.196 | 2110.9 | 454.3 | 372.2405 | 138562.96 | 3302.432 | 3204.121 | 828.0310 | 465.7977 | 216967.5 | 982.1244 | 962.256 | 121.5490 | 170.4273 | 29045.48 | 2.281250 | 2.25 | 0.975 | 0.7643897 | 0.5842917 |
Sim | 5.3375 | 5.3 | 0.675 | 0.5339048 | 0.2850543 | 28.95833 | 28.5 | 7.5 | 8.784765 | 77.17210 | 163.2083 | 137.0 | 87.00 | 96.31424 | 9276.433 | 67.03333 | 69.115 | 32.700 | 19.43964 | 377.8994 | 0.9651409 | 0.9313 | 0.25935 | 0.3403523 | 0.1158397 | 1.503227 | 1.0511 | 0.653175 | 2.3723368 | 5.6279820 | 0.1145182 | 0.0885 | 0.0423 | 0.0920361 | 0.0084706 | 2.457550 | 2.35830 | 1.082375 | 0.7704118 | 0.5935343 | 85.26087 | 86.0 | 16.5 | 14.33755 | 205.5652 | 86.65217 | 89.0 | 14.00 | 14.7328 | 217.0553 | 2831.291 | 2756.1 | 366.5 | 306.4685 | 93922.95 | 2102.757 | 2075.3 | 311.7 | 241.6251 | 58382.71 | 3474.131 | 3186.120 | 333.0125 | 983.9639 | 968184.9 | 1036.2419 | 1028.095 | 139.2735 | 136.0556 | 18511.12 | 2.505417 | 2.00 | 1.175 | 0.9896902 | 0.9794868 |
Correlação Ponto- Biserial - Sintomas vs Variáveis numéricas
Pearson's product-moment correlation
data: dados$Lep and dados$Classificacao_Sintomas_bin
t = -1.8837, df = 34, p-value = 0.06818
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
-0.57761091 0.02349755
sample estimates:
cor
-0.3074113
Variavel Correlacao Valor_p
tempo_Covid.cor tempo_Covid 0.12321513 0.44877242
HbGlic.cor HbGlic -0.21169203 0.18974892
VitD.cor VitD 0.08770475 0.59047828
Trig.cor Trig 0.03029670 0.85277449
CH50.cor CH50 -0.12750343 0.43301696
SOD.mg_ptn.cor SOD.mg_ptn -0.02170974 0.90148432
CAT.cor CAT 0.11765983 0.50085242
TBARs.cor TBARs 0.05847001 0.73865407
PTN_CARB.cor PTN_CARB 0.10346562 0.58638075
FEV1.pred.cor FEV1.pred -0.17293333 0.29243785
predFEV1post.cor predFEV1post -0.18726749 0.25363290
IL_10.cor IL_10 -0.11032501 0.52181598
Lep.cor Lep -0.30741133 0.06817916
TNF.cor TNF 0.10069463 0.55899560
IL_17A.cor IL_17A 0.17658048 0.30290888
corrplot 0.92 loaded