library(readxl)
library(latexpdf)
bd_elena <- read_excel("~/Desktop/2024_2025/TFGS/elena/bd_elena.xlsx")
#DATOS SOCIODEMOGRÁFICOS
library(sjPlot)
library(psych)
plot_frq(bd_elena$sexo)

bd_elena$curso<-factor(bd_elena$curso, levels = c("Primero", "Segundo", "Tercero", "Cuarto"))
plot_frq(bd_elena$curso)

plot_frq(bd_elena$cursor)

plot_frq(bd_elena$proce)

plot_frq(bd_elena$procer)

describeBy(bd_elena$edad)
## Warning in describeBy(bd_elena$edad): no grouping variable requested
#DATOS ANTECEDENTES DE ENFERMEDAD Y MEDICACIÓN
plot_frq(bd_elena$antecedentes)

table(bd_elena$ante_enfermedad)
## 
##                                asma                                Asma 
##                                   1                                   4 
##                                ASMA                    Asma instrinseca 
##                                   2                                   1 
##              asma por alergia polen                      Asma y alergia 
##                                   1                                   1 
## asma y alergia al polen y gramineas                       Asma, alergia 
##                                   1                                   1 
##              asma, cancer de pulmon                          bronquitis 
##                                   1                                   1 
##                     Cáncer, alergia                           Silicosis 
##                                   1                                   1
plot_frq(bd_elena$medicacion)

plot_frq(bd_elena$medicacion_tipo)

plot_frq(bd_elena$clinica)

plot_frq(bd_elena$N1a)

plot_frq(bd_elena$N1b)

plot_frq(bd_elena$N2a)

plot_frq(bd_elena$N2b)

#CONSUMO DE TABACO
plot_frq(bd_elena$N1)

plot_frq(bd_elena$N1R)

sjt.xtab(bd_elena$N1R, bd_elena$sexo, show.cell.prc = T, show.row.prc = T)
N1R sexo Total
Hombre Mujer
Fuma 4
23.5 %
3.9 % 		13
76.5 %
12.7 % 		17
100 %
16.6 %
No fuma 19
22.4 %
18.6 % 		66
77.6 %
64.7 % 		85
100 %
83.3 %
Total 23
22.5 %
22.5 % 		79
77.5 %
77.5 % 		102
100 %
100 %
χ2=0.000 · df=1 · &phi=0.010 · Fisher’s p=1.000 
sjt.xtab(bd_elena$N1R, bd_elena$cursor, show.cell.prc = T, show.row.prc = T)
N1R cursor Total
primero segundo
Fuma 6
35.3 %
5.9 % 		11
64.7 %
10.8 % 		17
100 %
16.7 %
No fuma 34
40 %
33.3 % 		51
60 %
50 % 		85
100 %
83.3 %
Total 40
39.2 %
39.2 % 		62
60.8 %
60.8 % 		102
100 %
100 %
χ2=0.008 · df=1 · &phi=0.036 · Fisher’s p=0.791 
sjt.xtab(bd_elena$N1R, bd_elena$procer, show.cell.prc = T, show.row.prc = T) #DIF
N1R procer Total
bachiller no bachiller
Fuma 5
29.4 %
4.9 % 		12
70.6 %
11.8 % 		17
100 %
16.7 %
No fuma 59
69.4 %
57.8 % 		26
30.6 %
25.5 % 		85
100 %
83.3 %
Total 64
62.7 %
62.7 % 		38
37.3 %
37.3 % 		102
100 %
100 %
χ2=8.061 · df=1 · &phi=0.308 · Fisher’s p=0.005 
sjt.xtab(bd_elena$N1R, bd_elena$antecedentes, show.cell.prc = T, show.row.prc = T)
N1R antecedentes Total
No Sí
Fuma 13
76.5 %
12.7 % 		4
23.5 %
3.9 % 		17
100 %
16.6 %
No fuma 74
87.1 %
72.5 % 		11
12.9 %
10.8 % 		85
100 %
83.3 %
Total 87
85.3 %
85.3 % 		15
14.7 %
14.7 % 		102
100 %
100 %
χ2=0.563 · df=1 · &phi=0.111 · Fisher’s p=0.270 
sjt.xtab(bd_elena$N1R, bd_elena$medicacion, show.cell.prc = T, show.row.prc = T)
N1R medicacion Total
No Sí
Fuma 14
82.4 %
13.7 % 		3
17.6 %
2.9 % 		17
100 %
16.6 %
No fuma 79
92.9 %
77.5 % 		6
7.1 %
5.9 % 		85
100 %
83.4 %
Total 93
91.2 %
91.2 % 		9
8.8 %
8.8 % 		102
100 %
100 %
χ2=0.877 · df=1 · &phi=0.139 · Fisher’s p=0.170 
#FUMADORES
describeBy(bd_elena$N14)
## Warning in describeBy(bd_elena$N14): no grouping variable requested
describeBy(bd_elena$N15)
## Warning in describeBy(bd_elena$N15): no grouping variable requested
plot_frq(bd_elena$N19)

plot_frq(bd_elena$N21)

plot_frq(bd_elena$N22)

## Preguntas del test de Fagerstrom
plot_frq(bd_elena$N23a)

plot_frq(bd_elena$N23b)

plot_frq(bd_elena$N23c)

plot_frq(bd_elena$N23d)

plot_frq(bd_elena$N23e)

plot_frq(bd_elena$N23f)

describeBy(bd_elena$FAG) #PUNTUACIÓN DE FAGERSTROM
## Warning in describeBy(bd_elena$FAG): no grouping variable requested
t.test(FAG~sexo, data=bd_elena)
## 
##  Welch Two Sample t-test
## 
## data:  FAG by sexo
## t = 0.14665, df = 5.1016, p-value = 0.889
## alternative hypothesis: true difference in means between group Hombre and group Mujer is not equal to 0
## 95 percent confidence interval:
##  -2.526847  2.834539
## sample estimates:
## mean in group Hombre  mean in group Mujer 
##             6.000000             5.846154
t.test(FAG~cursor, data=bd_elena)
## 
##  Welch Two Sample t-test
## 
## data:  FAG by cursor
## t = 0.44675, df = 7.1611, p-value = 0.6683
## alternative hypothesis: true difference in means between group primero and group segundo is not equal to 0
## 95 percent confidence interval:
##  -1.921027  2.821027
## sample estimates:
## mean in group primero mean in group segundo 
##                  6.20                  5.75
t.test(FAG~procer, data=bd_elena)
## 
##  Welch Two Sample t-test
## 
## data:  FAG by procer
## t = -0.31363, df = 4.9419, p-value = 0.7666
## alternative hypothesis: true difference in means between group bachiller and group no bachiller is not equal to 0
## 95 percent confidence interval:
##  -3.690159  2.890159
## sample estimates:
##    mean in group bachiller mean in group no bachiller 
##                        5.6                        6.0
t.test(FAG~antecedentes, data=bd_elena)
## 
##  Welch Two Sample t-test
## 
## data:  FAG by antecedentes
## t = -0.53893, df = 3.4672, p-value = 0.6226
## alternative hypothesis: true difference in means between group No and group Sí is not equal to 0
## 95 percent confidence interval:
##  -3.548278  2.453040
## sample estimates:
## mean in group No mean in group Sí 
##         5.785714         6.333333
t.test(FAG~medicacion, data=bd_elena)
## 
##  Welch Two Sample t-test
## 
## data:  FAG by medicacion
## t = -0.44531, df = 1.2052, p-value = 0.7228
## alternative hypothesis: true difference in means between group No and group Sí is not equal to 0
## 95 percent confidence interval:
##  -14.18562  12.78562
## sample estimates:
## mean in group No mean in group Sí 
##              5.8              6.5
## Preguntas del test de Richmond
plot_frq(bd_elena$N24a)

plot_frq(bd_elena$N24b)

plot_frq(bd_elena$N24c)

plot_frq(bd_elena$N24d)

describeBy(bd_elena$RICH) #PUNTUACIÓN TEST DE RICHMOND
## Warning in describeBy(bd_elena$RICH): no grouping variable requested
t.test(RICH~sexo, data=bd_elena)
## 
##  Welch Two Sample t-test
## 
## data:  RICH by sexo
## t = 0.9673, df = 14.993, p-value = 0.3487
## alternative hypothesis: true difference in means between group Hombre and group Mujer is not equal to 0
## 95 percent confidence interval:
##  -1.273032  3.388417
## sample estimates:
## mean in group Hombre  mean in group Mujer 
##             6.750000             5.692308
t.test(RICH~cursor, data=bd_elena)
## 
##  Welch Two Sample t-test
## 
## data:  RICH by cursor
## t = 0.35514, df = 6.6196, p-value = 0.7335
## alternative hypothesis: true difference in means between group primero and group segundo is not equal to 0
## 95 percent confidence interval:
##  -3.728751  5.028751
## sample estimates:
## mean in group primero mean in group segundo 
##                  6.40                  5.75
t.test(RICH~procer, data=bd_elena)
## 
##  Welch Two Sample t-test
## 
## data:  RICH by procer
## t = 0.67794, df = 12.723, p-value = 0.51
## alternative hypothesis: true difference in means between group bachiller and group no bachiller is not equal to 0
## 95 percent confidence interval:
##  -2.047480  3.914147
## sample estimates:
##    mean in group bachiller mean in group no bachiller 
##                   6.600000                   5.666667
t.test(RICH~antecedentes, data=bd_elena)
## 
##  Welch Two Sample t-test
## 
## data:  RICH by antecedentes
## t = -0.89948, df = 14.96, p-value = 0.3826
## alternative hypothesis: true difference in means between group No and group Sí is not equal to 0
## 95 percent confidence interval:
##  -2.968979  1.207074
## sample estimates:
## mean in group No mean in group Sí 
##         5.785714         6.666667
t.test(RICH~medicacion, data=bd_elena)
## 
##  Welch Two Sample t-test
## 
## data:  RICH by medicacion
## t = -0.63601, df = 9.6603, p-value = 0.5395
## alternative hypothesis: true difference in means between group No and group Sí is not equal to 0
## 95 percent confidence interval:
##  -2.862702  1.596035
## sample estimates:
## mean in group No mean in group Sí 
##         5.866667         6.500000