SEM_BAYES_CMAMA
Mauricio Hernandez Carrillo , coaut. Ronaldo
17/5/2022
Paquetes utilizados
Se hará uso de la base de datos recolectada la cual consta de 80 observaciones y 105 variables de mujeres con cáncer de mama en la ciudad de Cali, concretando algunos parámetros para las simulaciones y el MCMC para obtener la convergencia de los parámetros esperados. Donde se parametrizara el numero de muestras de calentamiento (BURNIN1), el número de iteraciones(SAMPLE1) y el numero de cadenas (NCHAINS1).
options(mc.cores = parallel::detectCores())
#options(future.globals.maxSize = 768 * 1024^2)
#ctv::install.views("HighPerformanceComputing", coreOnly = TRUE)
#ctv::update.views("HighPerformanceComputing")
#Sys.setenv(OPENCL_INC = "/path/to/opencl/headers/")
#Sys.setenv(OPENCL_LIB64 = "/path/to/opencl/library/x86_64")
set.seed(535535)
datos2 <- readRDS("data/datos2.RDS")
datos <- datos2
datos<-datos2%>%
mutate(her2_nega = if_else(datos$her2 == 2, 1, 0, NA_real_))
datos$her2_nega [1] 0 0 0 1 0 0 1 0 0 1 0 1 0 1 1 1 0 1 1 1 0 1 0 0 1 0 0 1 0 0 0 0 0 1 1 1 0 0
[39] 1 1 1 1 1 1 1 1 1 0 1 1 1 0 0 1 0 1 0 1 0 0 1 1 0 0 0 1 1 0 1 1 1 1 0 0 1 1
[77] 1 1 1 1set.seed(535535)
BURNIN1 = 12000 #3000
SAMPLE1 = 500 #6500
NCHAINS1 = 6 #6
#para cargar con menos numero de iteraciones y cadenas
BURNIN = 3000 # 2500
SAMPLE = 7000 # 6500
CHAINS = 6 # 6MODELOS PLANTEADOS
Modelos finales con 8000 muestras, 5000 de calentamiento y 10 cadenas, Todo usado para SEM BAYESIANO por medio de Cadenas de Markov de Monte Carlo. A partir del análisis de los modelos propuestos por Wilson & Cleary para predimiento confirmatorio basados en los estudios realizado la RELACIÓN ENTRE SÍNTOMAS, FUNCIONALIDAD, PERCEPCIÓN DE SALUD Y CALIDAD DE VIDA EN MUJERES CON CÁNCER DE MAMA SOMETIDAS A QUIMIOTERAPIA. CALI-COLOMBIA.
model_ref_bio_ind_sinedad <- '
# measurement model
funcionalidad =~ prior("normal(0,15)")*f_br23 + prior("normal(0,15)")*f_c30
sintomas =~ prior("normal(0,15)")*s_br23 + prior("normal(0,15)")*s_c30
biologicas =~ her2_pos + comorb + estadio_avz
# regressions
cv_gral ~ salud + sintomas + funcionalidad
salud ~ funcionalidad
funcionalidad ~ sintomas
sintomas ~ biologicas
# residual correlations
'
model_ref_bio_ind_sinedad_sinher2 <- '
# measurement model
funcionalidad =~ prior("normal(0,15)")*f_br23 + prior("normal(0,15)")*f_c30
sintomas =~ prior("normal(0,15)")*s_br23 + prior("normal(0,15)")*s_c30
biologicas =~ comorb + estadio_avz
# regressions
cv_gral ~ salud + sintomas + funcionalidad
salud ~ funcionalidad
funcionalidad ~ sintomas
sintomas ~ biologicas
# residual correlations
'
model_ref_bio_ind_sinedad_prior <- '
# measurement model
funcionalidad =~ prior("normal(0,15)")*f_br23 + prior("normal(0,15)")*f_c30
sintomas =~ prior("normal(0,15)")*s_br23 + prior("normal(0,15)")*s_c30
biologicas =~ comorb + prior("normal(-10,10)")*her2_pos + estadio_avz
# regressions
cv_gral ~ salud + sintomas + funcionalidad
salud ~ funcionalidad
funcionalidad ~ sintomas
sintomas ~ biologicas
# residual correlations
'
model_ref_bio_ind_sinedad_her2nega <- '
# measurement model
funcionalidad =~ prior("normal(0,15)")*f_br23 + prior("normal(0,15)")*f_c30
sintomas =~ prior("normal(0,15)")*s_br23 + prior("normal(0,15)")*s_c30
biologicas =~ comorb + estadio_avz + her2_nega
# regressions
cv_gral ~ salud + sintomas + funcionalidad
salud ~ funcionalidad
funcionalidad ~ sintomas
sintomas ~ biologicas
# residual correlations
'Exploracion de funcion bsem
De el paquete Blavaan que ayuda a ejecutar la estimacion de los modelos bayesianos para ecuaciones de modelos estructurales, por medio Markov Chain Monte Carlo (MCMC) el cual es un metodo de simulación para generar muestras de las distribuciones a posteriori y estimar cantidades de interes a posteriori.
set.seed(535535)
fitref_bio_ind_sinedad <- bsem(
model = model_ref_bio_ind_sinedad,
data = datos,
auto.var = TRUE,
auto.fix.first = TRUE,
auto.cov.lv.x = TRUE,
save.lvs = TRUE,
inits = "prior",
sample = SAMPLE1 ,
burnin = BURNIN1 ,
n.chains = NCHAINS1)Computing posterior predictives...set.seed(535535)
fitref_bio_ind_sinedad_sinher2 <- bsem(
model = model_ref_bio_ind_sinedad_sinher2,
data = datos,
auto.var = TRUE,
auto.fix.first = TRUE,
auto.cov.lv.x = TRUE,
save.lvs = TRUE,
inits = "prior",
sample = SAMPLE1 ,
burnin = BURNIN1,
n.chains = NCHAINS1)Computing posterior predictives...set.seed(535535)
fitref_bio_ind_sinedad_prior <- bsem(
model = model_ref_bio_ind_sinedad_prior,
data = datos,
auto.var = TRUE,
auto.fix.first = TRUE,
auto.cov.lv.x = TRUE,
save.lvs = TRUE,
inits = "prior",
sample = SAMPLE1,
burnin = BURNIN1,
n.chains = NCHAINS1)Computing posterior predictives...set.seed(535535)
fitref_model_ref_bio_ind_sinedad_her2nega <- bsem(
model = model_ref_bio_ind_sinedad_her2nega,
data = datos,
auto.var = TRUE,
auto.fix.first = TRUE,
auto.cov.lv.x = TRUE,
save.lvs = TRUE,
inits = "prior",
sample = SAMPLE1,
burnin = BURNIN1,
n.chains = NCHAINS1)Computing posterior predictives...Resumen del modelo
summary(fitref_bio_ind_sinedad,standardized = TRUE, rsquare=TRUE)#esta## blavaan (0.4-1) results of 500 samples after 12000 adapt/burnin iterations
##
## Number of observations 80
##
## Number of missing patterns 1
##
## Statistic MargLogLik PPP
## Value -719.918 0.066
##
## Latent Variables:
## Estimate Post.SD pi.lower pi.upper Std.lv Std.all
## funcionalidad =~
## f_br23 1.000 0.471 0.770
## f_c30 1.450 0.166 1.167 1.823 0.683 0.926
## sintomas =~
## s_br23 1.000 0.296 0.546
## s_c30 2.339 0.460 1.685 3.447 0.692 0.929
## biologicas =~
## her2_pos 1.000 0.033 0.064
## comorb -0.167 5.726 -13.495 11.956 -0.005 -0.011
## estadio_avz -1.236 9.994 -20.074 18.700 -0.040 -0.093
## Rhat Prior
##
##
## 1.005 normal(0,15)
##
##
## 1.003 normal(0,15)
##
##
## 1.001 normal(0,10)
## 1.020 normal(0,10)
##
## Regressions:
## Estimate Post.SD pi.lower pi.upper Std.lv Std.all
## cv_gral ~
## salud 0.759 0.066 0.628 0.892 0.759 0.786
## sintomas -0.946 5.689 -14.997 10.777 -0.280 -0.164
## funcionalidad 0.079 3.712 -8.697 7.867 0.037 0.022
## salud ~
## funcionalidad 2.603 0.391 1.891 3.435 1.226 0.695
## funcionalidad ~
## sintomas -1.539 0.338 -2.331 -1.031 -0.967 -0.967
## sintomas ~
## biologicas 0.764 8.619 -15.798 18.530 0.084 0.084
## Rhat Prior
##
## 1.006 normal(0,10)
## 1.012 normal(0,10)
## 1.012 normal(0,10)
##
## 1.003 normal(0,10)
##
## 1.003 normal(0,10)
##
## 1.009 normal(0,10)
##
## Intercepts:
## Estimate Post.SD pi.lower pi.upper Std.lv Std.all
## .f_br23 2.343 0.072 2.203 2.483 2.343 3.830
## .f_c30 2.438 0.086 2.272 2.606 2.438 3.307
## .s_br23 1.765 0.062 1.643 1.887 1.765 3.255
## .s_c30 2.162 0.088 1.992 2.337 2.162 2.901
## .her2_pos 0.437 0.058 0.321 0.553 0.437 0.859
## .comorb 0.338 0.058 0.229 0.453 0.338 0.704
## .estadio_avz 0.338 0.054 0.233 0.445 0.338 0.780
## .cv_gral 0.807 0.300 0.203 1.386 0.807 0.474
## .salud 4.341 0.207 3.933 4.750 4.341 2.460
## .funcionalidad 0.000 0.000 0.000
## .sintomas 0.000 0.000 0.000
## biologicas 0.000 0.000 0.000
## Rhat Prior
## 1.000 normal(0,32)
## 0.999 normal(0,32)
## 1.000 normal(0,32)
## 1.000 normal(0,32)
## 1.000 normal(0,32)
## 0.999 normal(0,32)
## 0.999 normal(0,32)
## 1.006 normal(0,10)
## 1.000 normal(0,10)
##
##
##
##
## Variances:
## Estimate Post.SD pi.lower pi.upper Std.lv Std.all
## .f_br23 0.152 0.028 0.105 0.215 0.152 0.407
## .f_c30 0.077 0.028 0.023 0.134 0.077 0.142
## .s_br23 0.206 0.036 0.147 0.287 0.206 0.702
## .s_c30 0.076 0.040 0.001 0.151 0.076 0.137
## .her2_pos 0.257 0.041 0.190 0.348 0.257 0.996
## .comorb 0.231 0.040 0.164 0.315 0.231 1.000
## .estadio_avz 0.186 0.072 0.003 0.294 0.186 0.991
## .cv_gral 0.437 0.110 0.160 0.638 0.437 0.151
## .salud 1.611 0.278 1.142 2.228 1.611 0.517
## .funcionalidad 0.014 0.017 0.000 0.058 0.065 0.065
## .sintomas 0.087 0.047 0.003 0.188 0.993 0.993
## biologicas 0.001 0.002 0.000 0.007 1.000 1.000
## Rhat Prior
## 1.002 gamma(1,.5)[sd]
## 1.001 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 1.005 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.020 gamma(1,.5)[sd]
## 1.011 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.008 gamma(1,.5)[sd]
## 1.004 gamma(1,.5)[sd]
## 1.002 gamma(1,.5)[sd]
##
## R-Square:
## Estimate
## f_br23 0.593
## f_c30 0.858
## s_br23 0.298
## s_c30 0.863
## her2_pos 0.004
## comorb 0.000
## estadio_avz 0.009
## cv_gral 0.849
## salud 0.483
## funcionalidad 0.935
## sintomas 0.007summary(fitref_bio_ind_sinedad_sinher2,standardized = TRUE, rsquare=TRUE)### ** WARNING ** blavaan (0.4-1) did NOT converge after 12000 adapt+burnin iterations
## ** WARNING ** Proceed with caution
##
## Number of observations 80
##
## Number of missing patterns 1
##
## Statistic MargLogLik PPP
## Value -1223.906 0.050
##
## Latent Variables:
## Estimate Post.SD pi.lower pi.upper Std.lv Std.all
## funcionalidad =~
## f_br23 1.000 0.330 0.586
## f_c30 -0.991 5.683 -16.929 1.791 -0.327 -0.771
## sintomas =~
## s_br23 1.000 0.253 0.465
## s_c30 -1.541 9.136 -27.587 3.651 -0.389 -0.836
## biologicas =~
## comorb 1.000 0.047 0.097
## estadio_avz -0.075 8.790 -16.817 17.157 -0.004 -0.008
## Rhat Prior
##
##
## 3.966 normal(0,15)
##
##
## 3.738 normal(0,15)
##
##
## 1.015 normal(0,10)
##
## Regressions:
## Estimate Post.SD pi.lower pi.upper Std.lv Std.all
## cv_gral ~
## salud 0.759 0.068 0.624 0.886 0.759 0.848
## sintomas -0.189 5.726 -12.039 13.700 -0.048 -0.039
## funcionalidad 0.345 3.984 -8.670 9.200 0.114 0.094
## salud ~
## funcionalidad -1.423 9.350 -27.747 3.445 -0.469 -0.347
## funcionalidad ~
## sintomas 1.216 5.629 -2.224 16.874 0.932 0.932
## sintomas ~
## biologicas -0.467 7.452 -16.264 15.045 -0.087 -0.087
## Rhat Prior
##
## 1.012 normal(0,10)
## 1.023 normal(0,10)
## 1.002 normal(0,10)
##
## 4.070 normal(0,10)
##
## 3.689 normal(0,10)
##
## 1.011 normal(0,10)
##
## Intercepts:
## Estimate Post.SD pi.lower pi.upper Std.lv Std.all
## .f_br23 2.341 0.074 2.199 2.487 2.341 4.158
## .f_c30 2.436 0.090 2.263 2.610 2.436 5.744
## .s_br23 1.766 0.066 1.636 1.901 1.766 3.247
## .s_c30 2.164 0.091 1.987 2.344 2.164 4.645
## .comorb 0.336 0.053 0.236 0.444 0.336 0.693
## .estadio_avz 0.337 0.057 0.225 0.449 0.337 0.794
## .cv_gral 0.807 0.306 0.220 1.408 0.807 0.666
## .salud 4.331 0.209 3.917 4.734 4.331 3.200
## .funcionalidad 0.000 0.000 0.000
## .sintomas 0.000 0.000 0.000
## biologicas 0.000 0.000 0.000
## Rhat Prior
## 1.002 normal(0,32)
## 1.002 normal(0,32)
## 1.002 normal(0,32)
## 1.002 normal(0,32)
## 1.000 normal(0,32)
## 0.999 normal(0,32)
## 1.011 normal(0,10)
## 1.000 normal(0,10)
##
##
##
##
## Variances:
## Estimate Post.SD pi.lower pi.upper Std.lv Std.all
## .f_br23 0.208 0.129 0.107 0.558 0.208 0.657
## .f_c30 0.073 0.030 0.013 0.137 0.073 0.406
## .s_br23 0.232 0.069 0.149 0.414 0.232 0.784
## .s_c30 0.065 0.042 0.000 0.143 0.065 0.301
## .comorb 0.233 0.038 0.171 0.317 0.233 0.991
## .estadio_avz 0.180 0.069 0.008 0.288 0.180 1.000
## .cv_gral 0.457 0.096 0.281 0.661 0.457 0.311
## .salud 1.612 0.284 1.137 2.219 1.612 0.880
## .funcionalidad 0.014 0.018 0.000 0.059 0.131 0.131
## .sintomas 0.063 0.052 0.000 0.177 0.992 0.992
## biologicas 0.002 0.005 0.000 0.014 1.000 1.000
## Rhat Prior
## 3.197 gamma(1,.5)[sd]
## 1.018 gamma(1,.5)[sd]
## 1.686 gamma(1,.5)[sd]
## 1.071 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.009 gamma(1,.5)[sd]
## 1.010 gamma(1,.5)[sd]
## 1.001 gamma(1,.5)[sd]
## 1.100 gamma(1,.5)[sd]
## 1.211 gamma(1,.5)[sd]
## 1.016 gamma(1,.5)[sd]
##
## R-Square:
## Estimate
## f_br23 0.343
## f_c30 0.594
## s_br23 0.216
## s_c30 0.699
## comorb 0.009
## estadio_avz 0.000
## cv_gral 0.689
## salud 0.120
## funcionalidad 0.869
## sintomas 0.008summary(fitref_bio_ind_sinedad_prior,standardized = TRUE, rsquare=TRUE)## blavaan (0.4-1) results of 500 samples after 12000 adapt/burnin iterations
##
## Number of observations 80
##
## Number of missing patterns 1
##
## Statistic MargLogLik PPP
## Value -719.199 0.064
##
## Latent Variables:
## Estimate Post.SD pi.lower pi.upper Std.lv Std.all
## funcionalidad =~
## f_br23 1.000 0.486 0.780
## f_c30 1.445 0.155 1.177 1.791 0.703 0.931
## sintomas =~
## s_br23 1.000 0.304 0.556
## s_c30 2.356 0.477 1.671 3.540 0.715 0.935
## biologicas =~
## comorb 1.000 0.029 0.061
## her2_pos -5.146 8.321 -26.282 7.819 -0.151 -0.291
## estadio_avz 1.619 9.677 -17.218 20.019 0.047 0.106
## Rhat Prior
##
##
## 1.001 normal(0,15)
##
##
## 1.004 normal(0,15)
##
##
## 1.012 normal(-10,10)
## 1.012 normal(0,10)
##
## Regressions:
## Estimate Post.SD pi.lower pi.upper Std.lv Std.all
## cv_gral ~
## salud 0.758 0.068 0.625 0.896 0.758 0.780
## sintomas -0.931 5.188 -13.418 10.241 -0.283 -0.162
## funcionalidad 0.113 3.399 -8.046 7.372 0.055 0.032
## salud ~
## funcionalidad 2.589 0.385 1.879 3.413 1.259 0.704
## funcionalidad ~
## sintomas -1.547 0.333 -2.298 -1.046 -0.966 -0.966
## sintomas ~
## biologicas -1.218 8.418 -17.782 15.876 -0.118 -0.118
## Rhat Prior
##
## 1.000 normal(0,10)
## 1.004 normal(0,10)
## 1.005 normal(0,10)
##
## 1.001 normal(0,10)
##
## 1.005 normal(0,10)
##
## 1.007 normal(0,10)
##
## Intercepts:
## Estimate Post.SD pi.lower pi.upper Std.lv Std.all
## .f_br23 2.341 0.071 2.201 2.480 2.341 3.755
## .f_c30 2.435 0.086 2.269 2.609 2.435 3.224
## .s_br23 1.765 0.061 1.646 1.885 1.765 3.232
## .s_c30 2.166 0.089 1.987 2.339 2.166 2.831
## .comorb 0.338 0.054 0.234 0.447 0.338 0.698
## .her2_pos 0.438 0.057 0.328 0.552 0.438 0.845
## .estadio_avz 0.338 0.056 0.228 0.448 0.338 0.758
## .cv_gral 0.813 0.305 0.185 1.403 0.813 0.467
## .salud 4.327 0.203 3.943 4.727 4.327 2.418
## .funcionalidad 0.000 0.000 0.000
## .sintomas 0.000 0.000 0.000
## biologicas 0.000 0.000 0.000
## Rhat Prior
## 1.005 normal(0,32)
## 1.005 normal(0,32)
## 1.001 normal(0,32)
## 1.005 normal(0,32)
## 1.001 normal(0,32)
## 1.000 normal(0,32)
## 1.000 normal(0,32)
## 1.000 normal(0,10)
## 1.005 normal(0,10)
##
##
##
##
## Variances:
## Estimate Post.SD pi.lower pi.upper Std.lv Std.all
## .f_br23 0.152 0.029 0.106 0.217 0.152 0.391
## .f_c30 0.076 0.027 0.025 0.134 0.076 0.133
## .s_br23 0.206 0.037 0.146 0.291 0.206 0.691
## .s_c30 0.074 0.040 0.001 0.147 0.074 0.126
## .comorb 0.234 0.038 0.169 0.321 0.234 0.996
## .her2_pos 0.246 0.056 0.105 0.349 0.246 0.915
## .estadio_avz 0.197 0.064 0.016 0.297 0.197 0.989
## .cv_gral 0.445 0.096 0.243 0.630 0.445 0.147
## .salud 1.615 0.288 1.151 2.278 1.615 0.504
## .funcionalidad 0.016 0.017 0.000 0.059 0.068 0.068
## .sintomas 0.091 0.047 0.004 0.191 0.986 0.986
## biologicas 0.001 0.002 0.000 0.005 1.000 1.000
## Rhat Prior
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.002 gamma(1,.5)[sd]
## 1.003 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.005 gamma(1,.5)[sd]
## 1.006 gamma(1,.5)[sd]
## 1.002 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.007 gamma(1,.5)[sd]
## 1.001 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
##
## R-Square:
## Estimate
## f_br23 0.609
## f_c30 0.867
## s_br23 0.309
## s_c30 0.874
## comorb 0.004
## her2_pos 0.085
## estadio_avz 0.011
## cv_gral 0.853
## salud 0.496
## funcionalidad 0.932
## sintomas 0.014summary(fitref_model_ref_bio_ind_sinedad_her2nega,standardized = TRUE, rsquare=TRUE)## blavaan (0.4-1) results of 500 samples after 12000 adapt/burnin iterations
##
## Number of observations 80
##
## Number of missing patterns 1
##
## Statistic MargLogLik PPP
## Value -720.042 0.071
##
## Latent Variables:
## Estimate Post.SD pi.lower pi.upper Std.lv Std.all
## funcionalidad =~
## f_br23 1.000 0.476 0.773
## f_c30 1.446 0.159 1.179 1.797 0.689 0.927
## sintomas =~
## s_br23 1.000 0.299 0.549
## s_c30 2.353 0.454 1.680 3.464 0.703 0.934
## biologicas =~
## comorb 1.000 0.032 0.067
## estadio_avz -1.148 9.551 -19.833 17.221 -0.037 -0.085
## her2_nega -0.036 6.252 -13.227 14.010 -0.001 -0.002
## Rhat Prior
##
##
## 1.001 normal(0,15)
##
##
## 1.001 normal(0,15)
##
##
## 1.008 normal(0,10)
## 1.002 normal(0,10)
##
## Regressions:
## Estimate Post.SD pi.lower pi.upper Std.lv Std.all
## cv_gral ~
## salud 0.758 0.066 0.626 0.889 0.758 0.777
## sintomas -0.674 5.455 -13.758 10.805 -0.201 -0.116
## funcionalidad 0.294 3.582 -8.509 8.357 0.140 0.081
## salud ~
## funcionalidad 2.596 0.382 1.908 3.400 1.236 0.698
## funcionalidad ~
## sintomas -1.538 0.316 -2.295 -1.047 -0.965 -0.965
## sintomas ~
## biologicas 0.247 8.689 -17.272 17.814 0.027 0.027
## Rhat Prior
##
## 1.001 normal(0,10)
## 1.004 normal(0,10)
## 1.004 normal(0,10)
##
## 1.000 normal(0,10)
##
## 1.003 normal(0,10)
##
## 1.009 normal(0,10)
##
## Intercepts:
## Estimate Post.SD pi.lower pi.upper Std.lv Std.all
## .f_br23 2.340 0.073 2.194 2.479 2.340 3.799
## .f_c30 2.434 0.088 2.264 2.611 2.434 3.277
## .s_br23 1.766 0.063 1.644 1.893 1.766 3.246
## .s_c30 2.167 0.090 1.984 2.343 2.167 2.879
## .comorb 0.337 0.053 0.233 0.444 0.337 0.695
## .estadio_avz 0.338 0.054 0.232 0.447 0.338 0.771
## .her2_nega 0.563 0.055 0.454 0.672 0.563 1.125
## .cv_gral 0.809 0.299 0.220 1.406 0.809 0.468
## .salud 4.331 0.208 3.924 4.744 4.331 2.446
## .funcionalidad 0.000 0.000 0.000
## .sintomas 0.000 0.000 0.000
## biologicas 0.000 0.000 0.000
## Rhat Prior
## 1.001 normal(0,32)
## 1.001 normal(0,32)
## 1.000 normal(0,32)
## 1.001 normal(0,32)
## 1.000 normal(0,32)
## 0.999 normal(0,32)
## 1.000 normal(0,32)
## 1.001 normal(0,10)
## 1.001 normal(0,10)
##
##
##
##
## Variances:
## Estimate Post.SD pi.lower pi.upper Std.lv Std.all
## .f_br23 0.153 0.029 0.106 0.217 0.153 0.402
## .f_c30 0.077 0.028 0.027 0.139 0.077 0.140
## .s_br23 0.207 0.036 0.149 0.287 0.207 0.699
## .s_c30 0.073 0.040 0.001 0.148 0.073 0.128
## .comorb 0.235 0.039 0.170 0.320 0.235 0.996
## .estadio_avz 0.191 0.063 0.015 0.291 0.191 0.993
## .her2_nega 0.250 0.047 0.165 0.349 0.250 1.000
## .cv_gral 0.443 0.101 0.216 0.649 0.443 0.148
## .salud 1.608 0.281 1.129 2.245 1.608 0.513
## .funcionalidad 0.016 0.017 0.000 0.059 0.069 0.069
## .sintomas 0.089 0.048 0.003 0.194 0.999 0.999
## biologicas 0.001 0.002 0.000 0.006 1.000 1.000
## Rhat Prior
## 1.000 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 0.999 gamma(1,.5)[sd]
## 1.003 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 1.004 gamma(1,.5)[sd]
## 1.001 gamma(1,.5)[sd]
## 1.003 gamma(1,.5)[sd]
## 1.000 gamma(1,.5)[sd]
## 1.004 gamma(1,.5)[sd]
## 1.001 gamma(1,.5)[sd]
## 1.007 gamma(1,.5)[sd]
##
## R-Square:
## Estimate
## f_br23 0.598
## f_c30 0.860
## s_br23 0.301
## s_c30 0.872
## comorb 0.004
## estadio_avz 0.007
## her2_nega 0.000
## cv_gral 0.852
## salud 0.487
## funcionalidad 0.931
## sintomas 0.001Informacion del BRMSEA
Para la evaciacion de ajuste para ecuacuones de modelos estructurales en un análisis factorial confirmatorio bayesiano con tamaños de muestras grandes.
El estudio muestra que el error cuadrático medio de aproximación de la raíz bayesiana recientemente propuesto
por metodo ppp valor p predictivo posteriores de las cadenas de markov
set.seed(535535)
blavFitIndices(fitref_bio_ind_sinedad)## Posterior mean (EAP) of devm-based fit indices:
##
## BRMSEA BGammaHat adjBGammaHat BMc
## 0.099 0.941 0.887 0.869blavFitIndices(fitref_bio_ind_sinedad_sinher2)## Posterior mean (EAP) of devm-based fit indices:
##
## BRMSEA BGammaHat adjBGammaHat BMc
## 0.222 0.898 0.467 0.798blavFitIndices(fitref_bio_ind_sinedad_prior)## Posterior mean (EAP) of devm-based fit indices:
##
## BRMSEA BGammaHat adjBGammaHat BMc
## 0.098 0.941 0.889 0.869blavFitIndices(fitref_model_ref_bio_ind_sinedad_her2nega)## Posterior mean (EAP) of devm-based fit indices:
##
## BRMSEA BGammaHat adjBGammaHat BMc
## 0.098 0.942 0.889 0.871summary(blavFitIndices(fitref_bio_ind_sinedad))##
## Posterior summary statistics and highest posterior density (HPD) 90% credible intervals for devm-based fit indices:
##
## EAP Median MAP SD lower upper
## BRMSEA 0.099 0.099 0.098 0.018 0.071 0.128
## BGammaHat 0.941 0.943 0.944 0.019 0.910 0.971
## adjBGammaHat 0.887 0.890 0.892 0.037 0.826 0.945
## BMc 0.869 0.872 0.874 0.042 0.799 0.935summary(blavFitIndices(fitref_bio_ind_sinedad_sinher2))##
## Posterior summary statistics and highest posterior density (HPD) 90% credible intervals for devm-based fit indices:
##
## EAP Median MAP SD lower upper
## BRMSEA 0.222 0.184 0.164 0.094 0.115 0.395
## BGammaHat 0.898 0.933 0.949 0.075 0.756 0.975
## adjBGammaHat 0.467 0.651 0.732 0.389 -0.277 0.870
## BMc 0.798 0.866 0.898 0.145 0.524 0.950summary(blavFitIndices(fitref_bio_ind_sinedad_prior))##
## Posterior summary statistics and highest posterior density (HPD) 90% credible intervals for devm-based fit indices:
##
## EAP Median MAP SD lower upper
## BRMSEA 0.098 0.098 0.101 0.017 0.068 0.124
## BGammaHat 0.941 0.942 0.943 0.019 0.914 0.974
## adjBGammaHat 0.889 0.891 0.893 0.035 0.837 0.951
## BMc 0.869 0.871 0.872 0.041 0.809 0.942summary(blavFitIndices(fitref_model_ref_bio_ind_sinedad_her2nega))##
## Posterior summary statistics and highest posterior density (HPD) 90% credible intervals for devm-based fit indices:
##
## EAP Median MAP SD lower upper
## BRMSEA 0.098 0.098 0.097 0.018 0.069 0.126
## BGammaHat 0.942 0.943 0.946 0.019 0.910 0.972
## adjBGammaHat 0.889 0.892 0.897 0.036 0.828 0.946
## BMc 0.871 0.874 0.880 0.042 0.801 0.937Informacion de R hat modelo de referencia
blavInspect(fitref_bio_ind_sinedad, 'rhat') funcionalidad=~f_c30 sintomas=~s_c30
1.0048315 1.0030244
biologicas=~comorb biologicas=~estadio_avz
1.0013575 1.0201912
cv_gral~salud cv_gral~sintomas
1.0056862 1.0119441
cv_gral~funcionalidad salud~funcionalidad
1.0118498 1.0028308
funcionalidad~sintomas sintomas~biologicas
1.0034780 1.0091393
f_br23~~f_br23 f_c30~~f_c30
1.0019487 1.0007276
s_br23~~s_br23 s_c30~~s_c30
0.9996431 1.0054009
her2_pos~~her2_pos comorb~~comorb
0.9994917 0.9994663
estadio_avz~~estadio_avz cv_gral~~cv_gral
1.0202822 1.0107859
salud~~salud funcionalidad~~funcionalidad
0.9992926 1.0084047
sintomas~~sintomas biologicas~~biologicas
1.0036061 1.0021398
f_br23~1 f_c30~1
1.0004614 0.9993499
s_br23~1 s_c30~1
0.9999890 0.9996622
her2_pos~1 comorb~1
0.9999089 0.9993346
estadio_avz~1 cv_gral~1
0.9994897 1.0055727
salud~1
1.0004099 blavInspect(fitref_bio_ind_sinedad_sinher2, 'rhat') funcionalidad=~f_c30 sintomas=~s_c30
3.9658109 3.7380204
biologicas=~estadio_avz cv_gral~salud
1.0153709 1.0119266
cv_gral~sintomas cv_gral~funcionalidad
1.0229883 1.0020759
salud~funcionalidad funcionalidad~sintomas
4.0700531 3.6888870
sintomas~biologicas f_br23~~f_br23
1.0106377 3.1965114
f_c30~~f_c30 s_br23~~s_br23
1.0184038 1.6859010
s_c30~~s_c30 comorb~~comorb
1.0708948 0.9994948
estadio_avz~~estadio_avz cv_gral~~cv_gral
1.0092397 1.0095816
salud~~salud funcionalidad~~funcionalidad
1.0014585 1.1002609
sintomas~~sintomas biologicas~~biologicas
1.2110571 1.0163587
f_br23~1 f_c30~1
1.0020289 1.0019791
s_br23~1 s_c30~1
1.0021137 1.0016088
comorb~1 estadio_avz~1
0.9996568 0.9988452
cv_gral~1 salud~1
1.0109300 1.0002102 blavInspect(fitref_bio_ind_sinedad_prior, 'rhat') funcionalidad=~f_c30 sintomas=~s_c30
1.0008893 1.0039595
biologicas=~her2_pos biologicas=~estadio_avz
1.0121161 1.0121729
cv_gral~salud cv_gral~sintomas
1.0002311 1.0036874
cv_gral~funcionalidad salud~funcionalidad
1.0046663 1.0013146
funcionalidad~sintomas sintomas~biologicas
1.0046516 1.0073331
f_br23~~f_br23 f_c30~~f_c30
0.9997050 0.9992521
s_br23~~s_br23 s_c30~~s_c30
1.0018637 1.0026322
comorb~~comorb her2_pos~~her2_pos
0.9993863 1.0051867
estadio_avz~~estadio_avz cv_gral~~cv_gral
1.0064925 1.0015101
salud~~salud funcionalidad~~funcionalidad
0.9989951 1.0065421
sintomas~~sintomas biologicas~~biologicas
1.0009603 0.9998795
f_br23~1 f_c30~1
1.0045834 1.0049751
s_br23~1 s_c30~1
1.0014623 1.0052806
comorb~1 her2_pos~1
1.0005511 0.9998580
estadio_avz~1 cv_gral~1
0.9995852 1.0002546
salud~1
1.0046504 Informacion del neff modelo de referencia
blavInspect(fitref_bio_ind_sinedad, 'neff') funcionalidad=~f_c30 sintomas=~s_c30
1350.0703 1194.6285
biologicas=~comorb biologicas=~estadio_avz
1687.1179 368.0325
cv_gral~salud cv_gral~sintomas
1391.6145 578.9260
cv_gral~funcionalidad salud~funcionalidad
562.8230 2027.5925
funcionalidad~sintomas sintomas~biologicas
1182.8548 616.4119
f_br23~~f_br23 f_c30~~f_c30
2970.8817 1772.8345
s_br23~~s_br23 s_c30~~s_c30
3465.0440 1128.2822
her2_pos~~her2_pos comorb~~comorb
3704.4874 3591.1805
estadio_avz~~estadio_avz cv_gral~~cv_gral
249.5160 494.7867
salud~~salud funcionalidad~~funcionalidad
3149.4470 899.0129
sintomas~~sintomas biologicas~~biologicas
1350.5927 1086.4631
f_br23~1 f_c30~1
1102.2056 928.0063
s_br23~1 s_c30~1
1494.5909 941.1430
her2_pos~1 comorb~1
3776.4438 3730.5295
estadio_avz~1 cv_gral~1
3702.1813 1382.5197
salud~1
1369.4601 blavInspect(fitref_bio_ind_sinedad_sinher2, 'neff') funcionalidad=~f_c30 sintomas=~s_c30
3.226636 3.249502
biologicas=~estadio_avz cv_gral~salud
332.836060 1176.299160
cv_gral~sintomas cv_gral~funcionalidad
636.717962 882.141737
salud~funcionalidad funcionalidad~sintomas
3.211005 3.259746
sintomas~biologicas f_br23~~f_br23
396.521406 3.319268
f_c30~~f_c30 s_br23~~s_br23
532.757716 4.613062
s_c30~~s_c30 comorb~~comorb
44.555081 2976.809758
estadio_avz~~estadio_avz cv_gral~~cv_gral
633.067872 1720.414514
salud~~salud funcionalidad~~funcionalidad
2667.499346 25.680187
sintomas~~sintomas biologicas~~biologicas
10.271901 853.343757
f_br23~1 f_c30~1
1313.836222 1029.692080
s_br23~1 s_c30~1
1608.358373 1026.979410
comorb~1 estadio_avz~1
3212.234455 2435.587433
cv_gral~1 salud~1
1191.404098 1208.385692 Graficos sem plot
semPaths(
fitref_bio_ind_sinedad,
intercepts = FALSE,
residuals = TRUE,
edge.label.cex = 1.5,
intStyle = "multi",
optimizeLatRes = TRUE,
title.color = "black",
groups = "lat",
pastel = TRUE,
exoVar = FALSE,
sizeInt = 5,
edge.color = "black",
esize = 6,
label.prop = 2,
sizeLat = 6,
"std"
)
semPaths(
fitref_bio_ind_sinedad_sinher2,
intercepts = FALSE,
residuals = TRUE,
edge.label.cex = 1.5,
intStyle = "multi",
optimizeLatRes = TRUE,
title.color = "black",
groups = "lat",
pastel = TRUE,
exoVar = FALSE,
sizeInt = 5,
edge.color = "black",
esize = 6,
label.prop = 2,
sizeLat = 6,
"std"
)
graficos de mcmc
plot(fitref_bio_ind_sinedad, par = 1:12, facet_args = list(ncol = 4))
plot(fitref_bio_ind_sinedad_sinher2, par = 1:12, facet_args = list(ncol = 4))
plot(fitref_bio_ind_sinedad_prior, par = 1:12, facet_args = list(ncol = 4))
plot(fitref_bio_ind_sinedad, plot.type = "intervals")
plot(fitref_bio_ind_sinedad, plot.type = "parcoord")
describe_posterior(fitref_bio_ind_sinedad)Summary of Posterior Distribution
Parameter | Component | Median | 95% CI | pd | ROPE | % in ROPE | Rhat | ESS
-----------------------------------------------------------------------------------------------------------------------------
funcionalidad=~f_c30 | latent | 1.43 | [ 1.15, 1.78] | 100% | [-0.10, 0.10] | 0% | 1.005 | 1350.00
sintomas=~s_c30 | latent | 2.26 | [ 1.64, 3.35] | 100% | [-0.10, 0.10] | 0% | 1.003 | 1195.00
biologicas=~comorb | latent | 0.10 | [-12.27, 12.65] | 51.63% | [-0.10, 0.10] | 3.23% | 1.001 | 1687.00
biologicas=~estadio_avz | latent | -2.22 | [-20.85, 17.86] | 57.30% | [-0.10, 0.10] | 0.49% | 1.020 | 368.00
cv_gral~salud | regression | 0.76 | [ 0.64, 0.90] | 100% | [-0.10, 0.10] | 0% | 1.006 | 1392.00
cv_gral~sintomas | regression | -0.63 | [-13.02, 11.77] | 60.87% | [-0.10, 0.10] | 3.72% | 1.012 | 579.00
cv_gral~funcionalidad | regression | 0.28 | [ -8.79, 7.54] | 56.93% | [-0.10, 0.10] | 4.84% | 1.012 | 563.00
salud~funcionalidad | regression | 2.58 | [ 1.84, 3.33] | 100% | [-0.10, 0.10] | 0% | 1.003 | 2028.00
funcionalidad~sintomas | regression | -1.48 | [ -2.24, -0.99] | 100% | [-0.10, 0.10] | 0% | 1.003 | 1183.00
sintomas~biologicas | regression | 1.45 | [-15.02, 19.06] | 57.27% | [-0.10, 0.10] | 0.84% | 1.009 | 616.00
f_br23~~f_br23 | residual | 0.15 | [ 0.10, 0.21] | 100% | [-0.10, 0.10] | 0% | 1.002 | 2971.00
f_c30~~f_c30 | residual | 0.08 | [ 0.02, 0.13] | 100% | [-0.10, 0.10] | 83.02% | 1.001 | 1773.00
s_br23~~s_br23 | residual | 0.20 | [ 0.14, 0.28] | 100% | [-0.10, 0.10] | 0% | 1.000 | 3465.00
s_c30~~s_c30 | residual | 0.08 | [ 0.00, 0.14] | 100% | [-0.10, 0.10] | 76.01% | 1.005 | 1128.00
her2_pos~~her2_pos | residual | 0.25 | [ 0.18, 0.34] | 100% | [-0.10, 0.10] | 0% | 0.999 | 3704.00
comorb~~comorb | residual | 0.23 | [ 0.16, 0.31] | 100% | [-0.10, 0.10] | 0% | 0.999 | 3591.00
estadio_avz~~estadio_avz | residual | 0.20 | [ 0.00, 0.28] | 100% | [-0.10, 0.10] | 13.43% | 1.020 | 250.00
cv_gral~~cv_gral | residual | 0.44 | [ 0.22, 0.66] | 100% | [-0.10, 0.10] | 0% | 1.011 | 495.00
salud~~salud | residual | 1.58 | [ 1.10, 2.16] | 100% | [-0.10, 0.10] | 0% | 0.999 | 3149.00
funcionalidad~~funcionalidad | residual | 7.39e-03 | [ 0.00, 0.05] | 100% | [-0.10, 0.10] | 100% | 1.008 | 899.00
sintomas~~sintomas | residual | 0.09 | [ 0.00, 0.17] | 100% | [-0.10, 0.10] | 65.59% | 1.004 | 1351.00
biologicas~~biologicas | residual | 4.18e-04 | [ 0.00, 0.00] | 100% | [-0.10, 0.10] | 100% | 1.002 | 1086.00
f_br23~1 | intercept | 2.34 | [ 2.21, 2.49] | 100% | [-0.10, 0.10] | 0% | 1.000 | 1102.00
f_c30~1 | intercept | 2.44 | [ 2.26, 2.59] | 100% | [-0.10, 0.10] | 0% | 0.999 | 928.00
s_br23~1 | intercept | 1.76 | [ 1.64, 1.88] | 100% | [-0.10, 0.10] | 0% | 1.000 | 1495.00
s_c30~1 | intercept | 2.16 | [ 2.00, 2.34] | 100% | [-0.10, 0.10] | 0% | 1.000 | 941.00
her2_pos~1 | intercept | 0.44 | [ 0.32, 0.55] | 100% | [-0.10, 0.10] | 0% | 1.000 | 3776.00
comorb~1 | intercept | 0.34 | [ 0.23, 0.45] | 100% | [-0.10, 0.10] | 0% | 0.999 | 3731.00
estadio_avz~1 | intercept | 0.34 | [ 0.23, 0.44] | 100% | [-0.10, 0.10] | 0% | 0.999 | 3702.00
cv_gral~1 | intercept | 0.81 | [ 0.16, 1.34] | 99.50% | [-0.10, 0.10] | 0% | 1.006 | 1383.00
salud~1 | intercept | 4.34 | [ 3.91, 4.72] | 100% | [-0.10, 0.10] | 0% | 1.000 | 1369.00describe_posterior(fitref_bio_ind_sinedad_sinher2)Summary of Posterior Distribution
Parameter | Component | Median | 95% CI | pd | ROPE | % in ROPE | Rhat | ESS
-----------------------------------------------------------------------------------------------------------------------------
funcionalidad=~f_c30 | latent | 1.41 | [-15.38, 1.98] | 83.33% | [-0.10, 0.10] | 0% | 3.966 | 3.00
sintomas=~s_c30 | latent | 2.19 | [-24.64, 4.43] | 83.33% | [-0.10, 0.10] | 0% | 3.738 | 3.00
biologicas=~estadio_avz | latent | 0.95 | [-17.37, 16.19] | 52.53% | [-0.10, 0.10] | 0.32% | 1.015 | 333.00
cv_gral~salud | regression | 0.76 | [ 0.62, 0.88] | 100% | [-0.10, 0.10] | 0% | 1.012 | 1176.00
cv_gral~sintomas | regression | -0.56 | [-13.58, 11.95] | 60.80% | [-0.10, 0.10] | 3.37% | 1.023 | 637.00
cv_gral~funcionalidad | regression | 0.38 | [ -8.34, 9.43] | 60.70% | [-0.10, 0.10] | 5.12% | 1.002 | 882.00
salud~funcionalidad | regression | 2.50 | [-24.27, 4.05] | 83.33% | [-0.10, 0.10] | 0% | 4.070 | 3.00
funcionalidad~sintomas | regression | -1.30 | [ -2.84, 15.35] | 66.67% | [-0.10, 0.10] | 0.98% | 3.689 | 3.00
sintomas~biologicas | regression | -0.16 | [-15.61, 15.35] | 50.93% | [-0.10, 0.10] | 1.05% | 1.011 | 397.00
f_br23~~f_br23 | residual | 0.16 | [ 0.10, 0.52] | 100% | [-0.10, 0.10] | 0.74% | 3.197 | 3.00
f_c30~~f_c30 | residual | 0.07 | [ 0.01, 0.13] | 100% | [-0.10, 0.10] | 85.09% | 1.018 | 533.00
s_br23~~s_br23 | residual | 0.21 | [ 0.14, 0.38] | 100% | [-0.10, 0.10] | 0% | 1.686 | 5.00
s_c30~~s_c30 | residual | 0.07 | [ 0.00, 0.13] | 100% | [-0.10, 0.10] | 82.01% | 1.071 | 45.00
comorb~~comorb | residual | 0.23 | [ 0.17, 0.31] | 100% | [-0.10, 0.10] | 0% | 0.999 | 2977.00
estadio_avz~~estadio_avz | residual | 0.19 | [ 0.00, 0.27] | 100% | [-0.10, 0.10] | 14.80% | 1.009 | 633.00
cv_gral~~cv_gral | residual | 0.45 | [ 0.29, 0.66] | 100% | [-0.10, 0.10] | 0% | 1.010 | 1720.00
salud~~salud | residual | 1.59 | [ 1.09, 2.14] | 100% | [-0.10, 0.10] | 0% | 1.001 | 2667.00
funcionalidad~~funcionalidad | residual | 6.18e-03 | [ 0.00, 0.05] | 100% | [-0.10, 0.10] | 100% | 1.100 | 26.00
sintomas~~sintomas | residual | 0.06 | [ 0.00, 0.16] | 100% | [-0.10, 0.10] | 79.59% | 1.211 | 10.00
biologicas~~biologicas | residual | 8.29e-04 | [ 0.00, 0.01] | 100% | [-0.10, 0.10] | 100% | 1.016 | 853.00
f_br23~1 | intercept | 2.34 | [ 2.20, 2.48] | 100% | [-0.10, 0.10] | 0% | 1.002 | 1314.00
f_c30~1 | intercept | 2.44 | [ 2.26, 2.61] | 100% | [-0.10, 0.10] | 0% | 1.002 | 1030.00
s_br23~1 | intercept | 1.76 | [ 1.63, 1.89] | 100% | [-0.10, 0.10] | 0% | 1.002 | 1608.00
s_c30~1 | intercept | 2.16 | [ 1.98, 2.33] | 100% | [-0.10, 0.10] | 0% | 1.002 | 1027.00
comorb~1 | intercept | 0.34 | [ 0.24, 0.44] | 100% | [-0.10, 0.10] | 0% | 1.000 | 3212.00
estadio_avz~1 | intercept | 0.34 | [ 0.22, 0.45] | 100% | [-0.10, 0.10] | 0% | 0.999 | 2436.00
cv_gral~1 | intercept | 0.80 | [ 0.24, 1.42] | 99.63% | [-0.10, 0.10] | 0% | 1.011 | 1191.00
salud~1 | intercept | 4.33 | [ 3.91, 4.73] | 100% | [-0.10, 0.10] | 0% | 1.000 | 1208.00describe_posterior(fitref_bio_ind_sinedad_prior)Summary of Posterior Distribution
Parameter | Component | Median | 95% CI | pd | ROPE | % in ROPE | Rhat | ESS
-----------------------------------------------------------------------------------------------------------------------------
funcionalidad=~f_c30 | latent | 1.43 | [ 1.15, 1.76] | 100% | [-0.10, 0.10] | 0% | 1.001 | 1966.00
sintomas=~s_c30 | latent | 2.28 | [ 1.57, 3.28] | 100% | [-0.10, 0.10] | 0% | 1.004 | 1174.00
biologicas=~her2_pos | latent | -3.05 | [-24.69, 8.71] | 73.53% | [-0.10, 0.10] | 1.65% | 1.012 | 772.00
biologicas=~estadio_avz | latent | 2.33 | [-17.35, 19.59] | 58.53% | [-0.10, 0.10] | 0.67% | 1.012 | 527.00
cv_gral~salud | regression | 0.76 | [ 0.62, 0.89] | 100% | [-0.10, 0.10] | 0% | 1.000 | 1985.00
cv_gral~sintomas | regression | -0.68 | [-12.74, 10.72] | 62.43% | [-0.10, 0.10] | 3.09% | 1.004 | 952.00
cv_gral~funcionalidad | regression | 0.27 | [ -8.14, 7.21] | 57.87% | [-0.10, 0.10] | 5.68% | 1.005 | 931.00
salud~funcionalidad | regression | 2.57 | [ 1.86, 3.37] | 100% | [-0.10, 0.10] | 0% | 1.001 | 2409.00
funcionalidad~sintomas | regression | -1.50 | [ -2.20, -1.00] | 100% | [-0.10, 0.10] | 0% | 1.005 | 1114.00
sintomas~biologicas | regression | -1.68 | [-19.06, 14.40] | 57.37% | [-0.10, 0.10] | 0.63% | 1.007 | 788.00
f_br23~~f_br23 | residual | 0.15 | [ 0.10, 0.21] | 100% | [-0.10, 0.10] | 0.21% | 1.000 | 3226.00
f_c30~~f_c30 | residual | 0.07 | [ 0.02, 0.13] | 100% | [-0.10, 0.10] | 84.22% | 0.999 | 2082.00
s_br23~~s_br23 | residual | 0.20 | [ 0.14, 0.28] | 100% | [-0.10, 0.10] | 0% | 1.002 | 3218.00
s_c30~~s_c30 | residual | 0.08 | [ 0.00, 0.14] | 100% | [-0.10, 0.10] | 76.89% | 1.003 | 1036.00
comorb~~comorb | residual | 0.23 | [ 0.16, 0.31] | 100% | [-0.10, 0.10] | 0% | 0.999 | 3747.00
her2_pos~~her2_pos | residual | 0.25 | [ 0.16, 0.37] | 100% | [-0.10, 0.10] | 0% | 1.005 | 466.00
estadio_avz~~estadio_avz | residual | 0.20 | [ 0.03, 0.30] | 100% | [-0.10, 0.10] | 5.26% | 1.006 | 557.00
cv_gral~~cv_gral | residual | 0.44 | [ 0.28, 0.65] | 100% | [-0.10, 0.10] | 0% | 1.002 | 1298.00
salud~~salud | residual | 1.59 | [ 1.11, 2.18] | 100% | [-0.10, 0.10] | 0% | 0.999 | 3474.00
funcionalidad~~funcionalidad | residual | 8.87e-03 | [ 0.00, 0.05] | 100% | [-0.10, 0.10] | 100% | 1.007 | 784.00
sintomas~~sintomas | residual | 0.09 | [ 0.00, 0.17] | 100% | [-0.10, 0.10] | 62.50% | 1.001 | 1285.00
biologicas~~biologicas | residual | 3.20e-04 | [ 0.00, 0.00] | 100% | [-0.10, 0.10] | 100% | 1.000 | 1838.00
f_br23~1 | intercept | 2.34 | [ 2.20, 2.47] | 100% | [-0.10, 0.10] | 0% | 1.005 | 1501.00
f_c30~1 | intercept | 2.43 | [ 2.28, 2.61] | 100% | [-0.10, 0.10] | 0% | 1.005 | 1339.00
s_br23~1 | intercept | 1.77 | [ 1.65, 1.89] | 100% | [-0.10, 0.10] | 0% | 1.001 | 2029.00
s_c30~1 | intercept | 2.17 | [ 1.98, 2.33] | 100% | [-0.10, 0.10] | 0% | 1.005 | 1377.00
comorb~1 | intercept | 0.34 | [ 0.24, 0.45] | 100% | [-0.10, 0.10] | 0% | 1.001 | 4084.00
her2_pos~1 | intercept | 0.44 | [ 0.34, 0.56] | 100% | [-0.10, 0.10] | 0% | 1.000 | 3772.00
estadio_avz~1 | intercept | 0.34 | [ 0.22, 0.45] | 100% | [-0.10, 0.10] | 0% | 1.000 | 4312.00
cv_gral~1 | intercept | 0.82 | [ 0.22, 1.42] | 99.47% | [-0.10, 0.10] | 0% | 1.000 | 1911.00
salud~1 | intercept | 4.32 | [ 3.93, 4.72] | 100% | [-0.10, 0.10] | 0% | 1.005 | 1704.00describe_posterior(fitref_model_ref_bio_ind_sinedad_her2nega)Summary of Posterior Distribution
Parameter | Component | Median | 95% CI | pd | ROPE | % in ROPE | Rhat | ESS
-----------------------------------------------------------------------------------------------------------------------------
funcionalidad=~f_c30 | latent | 1.43 | [ 1.17, 1.79] | 100% | [-0.10, 0.10] | 0% | 1.001 | 2115.00
sintomas=~s_c30 | latent | 2.29 | [ 1.55, 3.22] | 100% | [-0.10, 0.10] | 0% | 1.001 | 1288.00
biologicas=~estadio_avz | latent | -1.42 | [-18.99, 17.71] | 53.77% | [-0.10, 0.10] | 0.53% | 1.008 | 523.00
biologicas=~her2_nega | latent | -0.30 | [-13.17, 14.04] | 52.70% | [-0.10, 0.10] | 1.51% | 1.002 | 1475.00
cv_gral~salud | regression | 0.76 | [ 0.62, 0.88] | 100% | [-0.10, 0.10] | 0% | 1.001 | 1675.00
cv_gral~sintomas | regression | -0.49 | [-13.75, 10.90] | 59.57% | [-0.10, 0.10] | 3.54% | 1.004 | 781.00
cv_gral~funcionalidad | regression | 0.38 | [ -9.45, 7.19] | 60.33% | [-0.10, 0.10] | 4.91% | 1.004 | 770.00
salud~funcionalidad | regression | 2.57 | [ 1.86, 3.34] | 100% | [-0.10, 0.10] | 0% | 1.000 | 2391.00
funcionalidad~sintomas | regression | -1.50 | [ -2.16, -0.98] | 100% | [-0.10, 0.10] | 0% | 1.003 | 1389.00
sintomas~biologicas | regression | 0.72 | [-17.04, 17.95] | 52.93% | [-0.10, 0.10] | 0.74% | 1.009 | 667.00
f_br23~~f_br23 | residual | 0.15 | [ 0.10, 0.21] | 100% | [-0.10, 0.10] | 0.91% | 1.000 | 3323.00
f_c30~~f_c30 | residual | 0.08 | [ 0.02, 0.13] | 100% | [-0.10, 0.10] | 82.57% | 1.000 | 2701.00
s_br23~~s_br23 | residual | 0.20 | [ 0.14, 0.28] | 100% | [-0.10, 0.10] | 0% | 0.999 | 3913.00
s_c30~~s_c30 | residual | 0.08 | [ 0.00, 0.13] | 100% | [-0.10, 0.10] | 78.88% | 1.003 | 1076.00
comorb~~comorb | residual | 0.23 | [ 0.16, 0.31] | 100% | [-0.10, 0.10] | 0% | 1.000 | 3558.00
estadio_avz~~estadio_avz | residual | 0.20 | [ 0.03, 0.31] | 100% | [-0.10, 0.10] | 5.26% | 1.004 | 680.00
her2_nega~~her2_nega | residual | 0.25 | [ 0.17, 0.35] | 100% | [-0.10, 0.10] | 0% | 1.001 | 2096.00
cv_gral~~cv_gral | residual | 0.44 | [ 0.26, 0.67] | 100% | [-0.10, 0.10] | 0% | 1.003 | 1301.00
salud~~salud | residual | 1.58 | [ 1.12, 2.21] | 100% | [-0.10, 0.10] | 0% | 1.000 | 3132.00
funcionalidad~~funcionalidad | residual | 8.47e-03 | [ 0.00, 0.05] | 100% | [-0.10, 0.10] | 100% | 1.004 | 939.00
sintomas~~sintomas | residual | 0.09 | [ 0.00, 0.17] | 100% | [-0.10, 0.10] | 65.03% | 1.001 | 1380.00
biologicas~~biologicas | residual | 4.31e-04 | [ 0.00, 0.00] | 100% | [-0.10, 0.10] | 100% | 1.007 | 1253.00
f_br23~1 | intercept | 2.34 | [ 2.20, 2.48] | 100% | [-0.10, 0.10] | 0% | 1.001 | 1266.00
f_c30~1 | intercept | 2.43 | [ 2.27, 2.61] | 100% | [-0.10, 0.10] | 0% | 1.001 | 1072.00
s_br23~1 | intercept | 1.77 | [ 1.65, 1.90] | 100% | [-0.10, 0.10] | 0% | 1.000 | 1885.00
s_c30~1 | intercept | 2.17 | [ 1.98, 2.34] | 100% | [-0.10, 0.10] | 0% | 1.001 | 1149.00
comorb~1 | intercept | 0.34 | [ 0.24, 0.45] | 100% | [-0.10, 0.10] | 0% | 1.000 | 4158.00
estadio_avz~1 | intercept | 0.34 | [ 0.24, 0.45] | 100% | [-0.10, 0.10] | 0% | 0.999 | 3736.00
her2_nega~1 | intercept | 0.56 | [ 0.45, 0.67] | 100% | [-0.10, 0.10] | 0% | 1.000 | 3994.00
cv_gral~1 | intercept | 0.81 | [ 0.20, 1.39] | 99.77% | [-0.10, 0.10] | 0% | 1.001 | 1723.00
salud~1 | intercept | 4.33 | [ 3.94, 4.75] | 100% | [-0.10, 0.10] | 0% | 1.001 | 1395.00sexit(fitref_bio_ind_sinedad_sinher2)# Following the Sequential Effect eXistence and sIgnificance Testing (SEXIT) framework, we report the median of the posterior distribution and its 95% CI (Highest Density Interval), along the probability of direction (pd), the probability of significance and the probability of being large. The thresholds beyond which the effect is considered as significant (i.e., non-negligible) and large are |0.05| and |0.30|.
- funcionalidad=~f_c30 (Median = 1.41, 95% CI [-15.38, 1.98]) has a 83.33% probability of being positive (> 0), 83.33% of being significant (> 0.05), and 83.33% of being large (> 0.30)
- sintomas=~s_c30 (Median = 2.19, 95% CI [-24.64, 4.43]) has a 83.33% probability of being positive (> 0), 83.33% of being significant (> 0.05), and 83.33% of being large (> 0.30)
- biologicas=~estadio_avz (Median = 0.95, 95% CI [-17.37, 16.19]) has a 52.53% probability of being positive (> 0), 52.47% of being significant (> 0.05), and 51.73% of being large (> 0.30)
- cv_gral~salud (Median = 0.76, 95% CI [0.62, 0.88]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- cv_gral~sintomas (Median = -0.56, 95% CI [-13.58, 11.95]) has a 60.80% probability of being negative (< 0), 60.20% of being significant (< -0.05), and 54.93% of being large (< -0.30)
- cv_gral~funcionalidad (Median = 0.38, 95% CI [-8.34, 9.43]) has a 60.70% probability of being positive (> 0), 59.47% of being significant (> 0.05), and 52.20% of being large (> 0.30)
- salud~funcionalidad (Median = 2.50, 95% CI [-24.27, 4.05]) has a 83.33% probability of being positive (> 0), 83.33% of being significant (> 0.05), and 83.33% of being large (> 0.30)
- funcionalidad~sintomas (Median = -1.30, 95% CI [-2.84, 15.35]) has a 66.67% probability of being negative (< 0), 66.67% of being significant (< -0.05), and 66.67% of being large (< -0.30)
- sintomas~biologicas (Median = -0.16, 95% CI [-15.61, 15.35]) has a 50.93% probability of being negative (< 0), 50.80% of being significant (< -0.05), and 49.20% of being large (< -0.30)
- f_br23~~f_br23 (Median = 0.16, 95% CI [0.10, 0.52]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 16.73% of being large (> 0.30)
- f_c30~~f_c30 (Median = 0.07, 95% CI [8.76e-03, 0.13]) has a 100.00% probability of being positive (> 0), 78.50% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- s_br23~~s_br23 (Median = 0.21, 95% CI [0.14, 0.38]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 15.00% of being large (> 0.30)
- s_c30~~s_c30 (Median = 0.07, 95% CI [1.74e-08, 0.13]) has a 100.00% probability of being positive (> 0), 62.93% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- comorb~~comorb (Median = 0.23, 95% CI [0.17, 0.31]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 5.20% of being large (> 0.30)
- estadio_avz~~estadio_avz (Median = 0.19, 95% CI [8.75e-07, 0.27]) has a 100.00% probability of being positive (> 0), 92.43% of being significant (> 0.05), and 1.70% of being large (> 0.30)
- cv_gral~~cv_gral (Median = 0.45, 95% CI [0.29, 0.66]) has a 100.00% probability of being positive (> 0), 99.87% of being significant (> 0.05), and 96.47% of being large (> 0.30)
- salud~~salud (Median = 1.59, 95% CI [1.09, 2.14]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- funcionalidad~~funcionalidad (Median = 6.18e-03, 95% CI [1.31e-09, 0.05]) has a 100.00% probability of being positive (> 0), 5.13% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- sintomas~~sintomas (Median = 0.06, 95% CI [2.26e-07, 0.16]) has a 100.00% probability of being positive (> 0), 56.87% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- biologicas~~biologicas (Median = 8.29e-04, 95% CI [2.08e-11, 8.91e-03]) has a 100.00% probability of being positive (> 0), 0.17% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- f_br23~1 (Median = 2.34, 95% CI [2.20, 2.48]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- f_c30~1 (Median = 2.44, 95% CI [2.26, 2.61]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- s_br23~1 (Median = 1.76, 95% CI [1.63, 1.89]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- s_c30~1 (Median = 2.16, 95% CI [1.98, 2.33]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- comorb~1 (Median = 0.34, 95% CI [0.24, 0.44]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 74.80% of being large (> 0.30)
- estadio_avz~1 (Median = 0.34, 95% CI [0.22, 0.45]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 74.80% of being large (> 0.30)
- cv_gral~1 (Median = 0.80, 95% CI [0.24, 1.42]) has a 99.63% probability of being positive (> 0), 99.50% of being significant (> 0.05), and 95.50% of being large (> 0.30)
- salud~1 (Median = 4.33, 95% CI [3.91, 4.73]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
Parameter | Median | 95% CI | Direction | Significance (> |0.05|) | Large (> |0.30|)
-----------------------------------------------------------------------------------------------------------------------
funcionalidad=~f_c30 | 1.41 | [-15.38, 1.98] | 0.83 | 0.83 | 0.83
sintomas=~s_c30 | 2.19 | [-24.64, 4.43] | 0.83 | 0.83 | 0.83
biologicas=~estadio_avz | 0.95 | [-17.37, 16.19] | 0.53 | 0.52 | 0.52
cv_gral~salud | 0.76 | [0.62, 0.88] | 1.00 | 1.00 | 1.00
cv_gral~sintomas | -0.56 | [-13.58, 11.95] | 0.61 | 0.60 | 0.55
cv_gral~funcionalidad | 0.38 | [-8.34, 9.43] | 0.61 | 0.59 | 0.52
salud~funcionalidad | 2.50 | [-24.27, 4.05] | 0.83 | 0.83 | 0.83
funcionalidad~sintomas | -1.30 | [-2.84, 15.35] | 0.67 | 0.67 | 0.67
sintomas~biologicas | -0.16 | [-15.61, 15.35] | 0.51 | 0.51 | 0.49
f_br23~~f_br23 | 0.16 | [0.10, 0.52] | 1.00 | 1.00 | 0.17
f_c30~~f_c30 | 0.07 | [8.76e-03, 0.13] | 1.00 | 0.78 | 0.00
s_br23~~s_br23 | 0.21 | [0.14, 0.38] | 1.00 | 1.00 | 0.15
s_c30~~s_c30 | 0.07 | [1.74e-08, 0.13] | 1.00 | 0.63 | 0.00
comorb~~comorb | 0.23 | [0.17, 0.31] | 1.00 | 1.00 | 0.05
estadio_avz~~estadio_avz | 0.19 | [8.75e-07, 0.27] | 1.00 | 0.92 | 0.02
cv_gral~~cv_gral | 0.45 | [0.29, 0.66] | 1.00 | 1.00 | 0.96
salud~~salud | 1.59 | [1.09, 2.14] | 1.00 | 1.00 | 1.00
funcionalidad~~funcionalidad | 6.18e-03 | [1.31e-09, 0.05] | 1.00 | 0.05 | 0.00
sintomas~~sintomas | 0.06 | [2.26e-07, 0.16] | 1.00 | 0.57 | 0.00
biologicas~~biologicas | 8.29e-04 | [2.08e-11, 8.91e-03] | 1.00 | 1.67e-03 | 0.00
f_br23~1 | 2.34 | [2.20, 2.48] | 1.00 | 1.00 | 1.00
f_c30~1 | 2.44 | [2.26, 2.61] | 1.00 | 1.00 | 1.00
s_br23~1 | 1.76 | [1.63, 1.89] | 1.00 | 1.00 | 1.00
s_c30~1 | 2.16 | [1.98, 2.33] | 1.00 | 1.00 | 1.00
comorb~1 | 0.34 | [0.24, 0.44] | 1.00 | 1.00 | 0.75
estadio_avz~1 | 0.34 | [0.22, 0.45] | 1.00 | 1.00 | 0.75
cv_gral~1 | 0.80 | [0.24, 1.42] | 1.00 | 0.99 | 0.95
salud~1 | 4.33 | [3.91, 4.73] | 1.00 | 1.00 | 1.00sexit(fitref_bio_ind_sinedad)# Following the Sequential Effect eXistence and sIgnificance Testing (SEXIT) framework, we report the median of the posterior distribution and its 95% CI (Highest Density Interval), along the probability of direction (pd), the probability of significance and the probability of being large. The thresholds beyond which the effect is considered as significant (i.e., non-negligible) and large are |0.05| and |0.30|.
- funcionalidad=~f_c30 (Median = 1.43, 95% CI [1.15, 1.78]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- sintomas=~s_c30 (Median = 2.26, 95% CI [1.64, 3.35]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- biologicas=~comorb (Median = 0.10, 95% CI [-12.27, 12.65]) has a 51.63% probability of being positive (> 0), 50.87% of being significant (> 0.05), and 47.07% of being large (> 0.30)
- biologicas=~estadio_avz (Median = -2.22, 95% CI [-20.85, 17.86]) has a 57.30% probability of being negative (< 0), 57.23% of being significant (< -0.05), and 56.53% of being large (< -0.30)
- cv_gral~salud (Median = 0.76, 95% CI [0.64, 0.90]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- cv_gral~sintomas (Median = -0.63, 95% CI [-13.02, 11.77]) has a 60.87% probability of being negative (< 0), 60.07% of being significant (< -0.05), and 55.63% of being large (< -0.30)
- cv_gral~funcionalidad (Median = 0.28, 95% CI [-8.79, 7.54]) has a 56.93% probability of being positive (> 0), 55.77% of being significant (> 0.05), and 49.37% of being large (> 0.30)
- salud~funcionalidad (Median = 2.58, 95% CI [1.84, 3.33]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- funcionalidad~sintomas (Median = -1.48, 95% CI [-2.24, -0.99]) has a 100.00% probability of being negative (< 0), 100.00% of being significant (< -0.05), and 100.00% of being large (< -0.30)
- sintomas~biologicas (Median = 1.45, 95% CI [-15.02, 19.06]) has a 57.27% probability of being positive (> 0), 57.07% of being significant (> 0.05), and 56.27% of being large (> 0.30)
- f_br23~~f_br23 (Median = 0.15, 95% CI [0.10, 0.21]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 0.03% of being large (> 0.30)
- f_c30~~f_c30 (Median = 0.08, 95% CI [0.02, 0.13]) has a 100.00% probability of being positive (> 0), 84.43% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- s_br23~~s_br23 (Median = 0.20, 95% CI [0.14, 0.28]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 1.40% of being large (> 0.30)
- s_c30~~s_c30 (Median = 0.08, 95% CI [1.67e-06, 0.14]) has a 100.00% probability of being positive (> 0), 75.50% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- her2_pos~~her2_pos (Median = 0.25, 95% CI [0.18, 0.34]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 14.47% of being large (> 0.30)
- comorb~~comorb (Median = 0.23, 95% CI [0.16, 0.31]) has a 100.00% probability of being positive (> 0), 99.97% of being significant (> 0.05), and 5.20% of being large (> 0.30)
- estadio_avz~~estadio_avz (Median = 0.20, 95% CI [3.71e-07, 0.28]) has a 100.00% probability of being positive (> 0), 91.87% of being significant (> 0.05), and 1.90% of being large (> 0.30)
- cv_gral~~cv_gral (Median = 0.44, 95% CI [0.22, 0.66]) has a 100.00% probability of being positive (> 0), 98.73% of being significant (> 0.05), and 92.60% of being large (> 0.30)
- salud~~salud (Median = 1.58, 95% CI [1.10, 2.16]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- funcionalidad~~funcionalidad (Median = 7.39e-03, 95% CI [1.19e-08, 0.05]) has a 100.00% probability of being positive (> 0), 4.80% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- sintomas~~sintomas (Median = 0.09, 95% CI [9.46e-06, 0.17]) has a 100.00% probability of being positive (> 0), 77.90% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- biologicas~~biologicas (Median = 4.18e-04, 95% CI [2.30e-11, 4.61e-03]) has a 100.00% probability of being positive (> 0), 0.00% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- f_br23~1 (Median = 2.34, 95% CI [2.21, 2.49]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- f_c30~1 (Median = 2.44, 95% CI [2.26, 2.59]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- s_br23~1 (Median = 1.76, 95% CI [1.64, 1.88]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- s_c30~1 (Median = 2.16, 95% CI [2.00, 2.34]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- her2_pos~1 (Median = 0.44, 95% CI [0.32, 0.55]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 98.90% of being large (> 0.30)
- comorb~1 (Median = 0.34, 95% CI [0.23, 0.45]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 74.40% of being large (> 0.30)
- estadio_avz~1 (Median = 0.34, 95% CI [0.23, 0.44]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 76.17% of being large (> 0.30)
- cv_gral~1 (Median = 0.81, 95% CI [0.16, 1.34]) has a 99.50% probability of being positive (> 0), 99.17% of being significant (> 0.05), and 95.07% of being large (> 0.30)
- salud~1 (Median = 4.34, 95% CI [3.91, 4.72]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
Parameter | Median | 95% CI | Direction | Significance (> |0.05|) | Large (> |0.30|)
-----------------------------------------------------------------------------------------------------------------------
funcionalidad=~f_c30 | 1.43 | [1.15, 1.78] | 1.00 | 1.00 | 1.00
sintomas=~s_c30 | 2.26 | [1.64, 3.35] | 1.00 | 1.00 | 1.00
biologicas=~comorb | 0.10 | [-12.27, 12.65] | 0.52 | 0.51 | 0.47
biologicas=~estadio_avz | -2.22 | [-20.85, 17.86] | 0.57 | 0.57 | 0.57
cv_gral~salud | 0.76 | [0.64, 0.90] | 1.00 | 1.00 | 1.00
cv_gral~sintomas | -0.63 | [-13.02, 11.77] | 0.61 | 0.60 | 0.56
cv_gral~funcionalidad | 0.28 | [-8.79, 7.54] | 0.57 | 0.56 | 0.49
salud~funcionalidad | 2.58 | [1.84, 3.33] | 1.00 | 1.00 | 1.00
funcionalidad~sintomas | -1.48 | [-2.24, -0.99] | 1.00 | 1.00 | 1.00
sintomas~biologicas | 1.45 | [-15.02, 19.06] | 0.57 | 0.57 | 0.56
f_br23~~f_br23 | 0.15 | [0.10, 0.21] | 1.00 | 1.00 | 3.33e-04
f_c30~~f_c30 | 0.08 | [0.02, 0.13] | 1.00 | 0.84 | 0.00
s_br23~~s_br23 | 0.20 | [0.14, 0.28] | 1.00 | 1.00 | 0.01
s_c30~~s_c30 | 0.08 | [1.67e-06, 0.14] | 1.00 | 0.76 | 0.00
her2_pos~~her2_pos | 0.25 | [0.18, 0.34] | 1.00 | 1.00 | 0.14
comorb~~comorb | 0.23 | [0.16, 0.31] | 1.00 | 1.00 | 0.05
estadio_avz~~estadio_avz | 0.20 | [3.71e-07, 0.28] | 1.00 | 0.92 | 0.02
cv_gral~~cv_gral | 0.44 | [0.22, 0.66] | 1.00 | 0.99 | 0.93
salud~~salud | 1.58 | [1.10, 2.16] | 1.00 | 1.00 | 1.00
funcionalidad~~funcionalidad | 7.39e-03 | [1.19e-08, 0.05] | 1.00 | 0.05 | 0.00
sintomas~~sintomas | 0.09 | [9.46e-06, 0.17] | 1.00 | 0.78 | 0.00
biologicas~~biologicas | 4.18e-04 | [2.30e-11, 4.61e-03] | 1.00 | 0.00 | 0.00
f_br23~1 | 2.34 | [2.21, 2.49] | 1.00 | 1.00 | 1.00
f_c30~1 | 2.44 | [2.26, 2.59] | 1.00 | 1.00 | 1.00
s_br23~1 | 1.76 | [1.64, 1.88] | 1.00 | 1.00 | 1.00
s_c30~1 | 2.16 | [2.00, 2.34] | 1.00 | 1.00 | 1.00
her2_pos~1 | 0.44 | [0.32, 0.55] | 1.00 | 1.00 | 0.99
comorb~1 | 0.34 | [0.23, 0.45] | 1.00 | 1.00 | 0.74
estadio_avz~1 | 0.34 | [0.23, 0.44] | 1.00 | 1.00 | 0.76
cv_gral~1 | 0.81 | [0.16, 1.34] | 0.99 | 0.99 | 0.95
salud~1 | 4.34 | [3.91, 4.72] | 1.00 | 1.00 | 1.00sexit(fitref_bio_ind_sinedad_prior)# Following the Sequential Effect eXistence and sIgnificance Testing (SEXIT) framework, we report the median of the posterior distribution and its 95% CI (Highest Density Interval), along the probability of direction (pd), the probability of significance and the probability of being large. The thresholds beyond which the effect is considered as significant (i.e., non-negligible) and large are |0.05| and |0.30|.
- funcionalidad=~f_c30 (Median = 1.43, 95% CI [1.15, 1.76]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- sintomas=~s_c30 (Median = 2.28, 95% CI [1.57, 3.28]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- biologicas=~her2_pos (Median = -3.05, 95% CI [-24.69, 8.71]) has a 73.53% probability of being negative (< 0), 73.00% of being significant (< -0.05), and 70.60% of being large (< -0.30)
- biologicas=~estadio_avz (Median = 2.33, 95% CI [-17.35, 19.59]) has a 58.53% probability of being positive (> 0), 58.43% of being significant (> 0.05), and 57.43% of being large (> 0.30)
- cv_gral~salud (Median = 0.76, 95% CI [0.62, 0.89]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- cv_gral~sintomas (Median = -0.68, 95% CI [-12.74, 10.72]) has a 62.43% probability of being negative (< 0), 61.40% of being significant (< -0.05), and 57.13% of being large (< -0.30)
- cv_gral~funcionalidad (Median = 0.27, 95% CI [-8.14, 7.21]) has a 57.87% probability of being positive (> 0), 56.57% of being significant (> 0.05), and 49.30% of being large (> 0.30)
- salud~funcionalidad (Median = 2.57, 95% CI [1.86, 3.37]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- funcionalidad~sintomas (Median = -1.50, 95% CI [-2.20, -1.00]) has a 100.00% probability of being negative (< 0), 100.00% of being significant (< -0.05), and 100.00% of being large (< -0.30)
- sintomas~biologicas (Median = -1.68, 95% CI [-19.06, 14.40]) has a 57.37% probability of being negative (< 0), 57.30% of being significant (< -0.05), and 56.60% of being large (< -0.30)
- f_br23~~f_br23 (Median = 0.15, 95% CI [0.10, 0.21]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 0.03% of being large (> 0.30)
- f_c30~~f_c30 (Median = 0.07, 95% CI [0.02, 0.13]) has a 100.00% probability of being positive (> 0), 84.23% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- s_br23~~s_br23 (Median = 0.20, 95% CI [0.14, 0.28]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 1.70% of being large (> 0.30)
- s_c30~~s_c30 (Median = 0.08, 95% CI [6.56e-09, 0.14]) has a 100.00% probability of being positive (> 0), 72.63% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- comorb~~comorb (Median = 0.23, 95% CI [0.16, 0.31]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 5.50% of being large (> 0.30)
- her2_pos~~her2_pos (Median = 0.25, 95% CI [0.16, 0.37]) has a 100.00% probability of being positive (> 0), 98.47% of being significant (> 0.05), and 13.63% of being large (> 0.30)
- estadio_avz~~estadio_avz (Median = 0.20, 95% CI [0.03, 0.30]) has a 100.00% probability of being positive (> 0), 95.60% of being significant (> 0.05), and 2.20% of being large (> 0.30)
- cv_gral~~cv_gral (Median = 0.44, 95% CI [0.28, 0.65]) has a 100.00% probability of being positive (> 0), 99.67% of being significant (> 0.05), and 95.13% of being large (> 0.30)
- salud~~salud (Median = 1.59, 95% CI [1.11, 2.18]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- funcionalidad~~funcionalidad (Median = 8.87e-03, 95% CI [1.97e-08, 0.05]) has a 100.00% probability of being positive (> 0), 5.53% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- sintomas~~sintomas (Median = 0.09, 95% CI [4.94e-08, 0.17]) has a 100.00% probability of being positive (> 0), 80.90% of being significant (> 0.05), and 0.07% of being large (> 0.30)
- biologicas~~biologicas (Median = 3.20e-04, 95% CI [8.22e-10, 3.22e-03]) has a 100.00% probability of being positive (> 0), 0.03% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- f_br23~1 (Median = 2.34, 95% CI [2.20, 2.47]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- f_c30~1 (Median = 2.43, 95% CI [2.28, 2.61]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- s_br23~1 (Median = 1.77, 95% CI [1.65, 1.89]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- s_c30~1 (Median = 2.17, 95% CI [1.98, 2.33]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- comorb~1 (Median = 0.34, 95% CI [0.24, 0.45]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 76.43% of being large (> 0.30)
- her2_pos~1 (Median = 0.44, 95% CI [0.34, 0.56]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 99.13% of being large (> 0.30)
- estadio_avz~1 (Median = 0.34, 95% CI [0.22, 0.45]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 74.90% of being large (> 0.30)
- cv_gral~1 (Median = 0.82, 95% CI [0.22, 1.42]) has a 99.47% probability of being positive (> 0), 99.20% of being significant (> 0.05), and 95.27% of being large (> 0.30)
- salud~1 (Median = 4.32, 95% CI [3.93, 4.72]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
Parameter | Median | 95% CI | Direction | Significance (> |0.05|) | Large (> |0.30|)
-----------------------------------------------------------------------------------------------------------------------
funcionalidad=~f_c30 | 1.43 | [1.15, 1.76] | 1.00 | 1.00 | 1.00
sintomas=~s_c30 | 2.28 | [1.57, 3.28] | 1.00 | 1.00 | 1.00
biologicas=~her2_pos | -3.05 | [-24.69, 8.71] | 0.74 | 0.73 | 0.71
biologicas=~estadio_avz | 2.33 | [-17.35, 19.59] | 0.59 | 0.58 | 0.57
cv_gral~salud | 0.76 | [0.62, 0.89] | 1.00 | 1.00 | 1.00
cv_gral~sintomas | -0.68 | [-12.74, 10.72] | 0.62 | 0.61 | 0.57
cv_gral~funcionalidad | 0.27 | [-8.14, 7.21] | 0.58 | 0.57 | 0.49
salud~funcionalidad | 2.57 | [1.86, 3.37] | 1.00 | 1.00 | 1.00
funcionalidad~sintomas | -1.50 | [-2.20, -1.00] | 1.00 | 1.00 | 1.00
sintomas~biologicas | -1.68 | [-19.06, 14.40] | 0.57 | 0.57 | 0.57
f_br23~~f_br23 | 0.15 | [0.10, 0.21] | 1.00 | 1.00 | 3.33e-04
f_c30~~f_c30 | 0.07 | [0.02, 0.13] | 1.00 | 0.84 | 0.00
s_br23~~s_br23 | 0.20 | [0.14, 0.28] | 1.00 | 1.00 | 0.02
s_c30~~s_c30 | 0.08 | [6.56e-09, 0.14] | 1.00 | 0.73 | 0.00
comorb~~comorb | 0.23 | [0.16, 0.31] | 1.00 | 1.00 | 0.06
her2_pos~~her2_pos | 0.25 | [0.16, 0.37] | 1.00 | 0.98 | 0.14
estadio_avz~~estadio_avz | 0.20 | [0.03, 0.30] | 1.00 | 0.96 | 0.02
cv_gral~~cv_gral | 0.44 | [0.28, 0.65] | 1.00 | 1.00 | 0.95
salud~~salud | 1.59 | [1.11, 2.18] | 1.00 | 1.00 | 1.00
funcionalidad~~funcionalidad | 8.87e-03 | [1.97e-08, 0.05] | 1.00 | 0.06 | 0.00
sintomas~~sintomas | 0.09 | [4.94e-08, 0.17] | 1.00 | 0.81 | 6.67e-04
biologicas~~biologicas | 3.20e-04 | [8.22e-10, 3.22e-03] | 1.00 | 3.33e-04 | 0.00
f_br23~1 | 2.34 | [2.20, 2.47] | 1.00 | 1.00 | 1.00
f_c30~1 | 2.43 | [2.28, 2.61] | 1.00 | 1.00 | 1.00
s_br23~1 | 1.77 | [1.65, 1.89] | 1.00 | 1.00 | 1.00
s_c30~1 | 2.17 | [1.98, 2.33] | 1.00 | 1.00 | 1.00
comorb~1 | 0.34 | [0.24, 0.45] | 1.00 | 1.00 | 0.76
her2_pos~1 | 0.44 | [0.34, 0.56] | 1.00 | 1.00 | 0.99
estadio_avz~1 | 0.34 | [0.22, 0.45] | 1.00 | 1.00 | 0.75
cv_gral~1 | 0.82 | [0.22, 1.42] | 0.99 | 0.99 | 0.95
salud~1 | 4.32 | [3.93, 4.72] | 1.00 | 1.00 | 1.00sexit(fitref_model_ref_bio_ind_sinedad_her2nega)# Following the Sequential Effect eXistence and sIgnificance Testing (SEXIT) framework, we report the median of the posterior distribution and its 95% CI (Highest Density Interval), along the probability of direction (pd), the probability of significance and the probability of being large. The thresholds beyond which the effect is considered as significant (i.e., non-negligible) and large are |0.05| and |0.30|.
- funcionalidad=~f_c30 (Median = 1.43, 95% CI [1.17, 1.79]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- sintomas=~s_c30 (Median = 2.29, 95% CI [1.55, 3.22]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- biologicas=~estadio_avz (Median = -1.42, 95% CI [-18.99, 17.71]) has a 53.77% probability of being negative (< 0), 53.70% of being significant (< -0.05), and 53.03% of being large (< -0.30)
- biologicas=~her2_nega (Median = -0.30, 95% CI [-13.17, 14.04]) has a 52.70% probability of being negative (< 0), 52.33% of being significant (< -0.05), and 50.00% of being large (< -0.30)
- cv_gral~salud (Median = 0.76, 95% CI [0.62, 0.88]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- cv_gral~sintomas (Median = -0.49, 95% CI [-13.75, 10.90]) has a 59.57% probability of being negative (< 0), 58.67% of being significant (< -0.05), and 54.00% of being large (< -0.30)
- cv_gral~funcionalidad (Median = 0.38, 95% CI [-9.45, 7.19]) has a 60.33% probability of being positive (> 0), 59.23% of being significant (> 0.05), and 52.40% of being large (> 0.30)
- salud~funcionalidad (Median = 2.57, 95% CI [1.86, 3.34]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- funcionalidad~sintomas (Median = -1.50, 95% CI [-2.16, -0.98]) has a 100.00% probability of being negative (< 0), 100.00% of being significant (< -0.05), and 100.00% of being large (< -0.30)
- sintomas~biologicas (Median = 0.72, 95% CI [-17.04, 17.95]) has a 52.93% probability of being positive (> 0), 52.77% of being significant (> 0.05), and 51.93% of being large (> 0.30)
- f_br23~~f_br23 (Median = 0.15, 95% CI [0.10, 0.21]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- f_c30~~f_c30 (Median = 0.08, 95% CI [0.02, 0.13]) has a 100.00% probability of being positive (> 0), 84.90% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- s_br23~~s_br23 (Median = 0.20, 95% CI [0.14, 0.28]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 1.70% of being large (> 0.30)
- s_c30~~s_c30 (Median = 0.08, 95% CI [4.64e-07, 0.13]) has a 100.00% probability of being positive (> 0), 72.47% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- comorb~~comorb (Median = 0.23, 95% CI [0.16, 0.31]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 5.93% of being large (> 0.30)
- estadio_avz~~estadio_avz (Median = 0.20, 95% CI [0.03, 0.31]) has a 100.00% probability of being positive (> 0), 95.30% of being significant (> 0.05), and 1.97% of being large (> 0.30)
- her2_nega~~her2_nega (Median = 0.25, 95% CI [0.17, 0.35]) has a 100.00% probability of being positive (> 0), 99.87% of being significant (> 0.05), and 13.17% of being large (> 0.30)
- cv_gral~~cv_gral (Median = 0.44, 95% CI [0.26, 0.67]) has a 100.00% probability of being positive (> 0), 99.70% of being significant (> 0.05), and 93.63% of being large (> 0.30)
- salud~~salud (Median = 1.58, 95% CI [1.12, 2.21]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- funcionalidad~~funcionalidad (Median = 8.47e-03, 95% CI [2.43e-09, 0.05]) has a 100.00% probability of being positive (> 0), 5.60% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- sintomas~~sintomas (Median = 0.09, 95% CI [3.11e-05, 0.17]) has a 100.00% probability of being positive (> 0), 79.73% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- biologicas~~biologicas (Median = 4.31e-04, 95% CI [1.02e-10, 3.90e-03]) has a 100.00% probability of being positive (> 0), 0.00% of being significant (> 0.05), and 0.00% of being large (> 0.30)
- f_br23~1 (Median = 2.34, 95% CI [2.20, 2.48]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- f_c30~1 (Median = 2.43, 95% CI [2.27, 2.61]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- s_br23~1 (Median = 1.77, 95% CI [1.65, 1.90]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- s_c30~1 (Median = 2.17, 95% CI [1.98, 2.34]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- comorb~1 (Median = 0.34, 95% CI [0.24, 0.45]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 76.30% of being large (> 0.30)
- estadio_avz~1 (Median = 0.34, 95% CI [0.24, 0.45]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 76.10% of being large (> 0.30)
- her2_nega~1 (Median = 0.56, 95% CI [0.45, 0.67]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
- cv_gral~1 (Median = 0.81, 95% CI [0.20, 1.39]) has a 99.77% probability of being positive (> 0), 99.63% of being significant (> 0.05), and 95.83% of being large (> 0.30)
- salud~1 (Median = 4.33, 95% CI [3.94, 4.75]) has a 100.00% probability of being positive (> 0), 100.00% of being significant (> 0.05), and 100.00% of being large (> 0.30)
Parameter | Median | 95% CI | Direction | Significance (> |0.05|) | Large (> |0.30|)
-----------------------------------------------------------------------------------------------------------------------
funcionalidad=~f_c30 | 1.43 | [1.17, 1.79] | 1.00 | 1.00 | 1.00
sintomas=~s_c30 | 2.29 | [1.55, 3.22] | 1.00 | 1.00 | 1.00
biologicas=~estadio_avz | -1.42 | [-18.99, 17.71] | 0.54 | 0.54 | 0.53
biologicas=~her2_nega | -0.30 | [-13.17, 14.04] | 0.53 | 0.52 | 0.50
cv_gral~salud | 0.76 | [0.62, 0.88] | 1.00 | 1.00 | 1.00
cv_gral~sintomas | -0.49 | [-13.75, 10.90] | 0.60 | 0.59 | 0.54
cv_gral~funcionalidad | 0.38 | [-9.45, 7.19] | 0.60 | 0.59 | 0.52
salud~funcionalidad | 2.57 | [1.86, 3.34] | 1.00 | 1.00 | 1.00
funcionalidad~sintomas | -1.50 | [-2.16, -0.98] | 1.00 | 1.00 | 1.00
sintomas~biologicas | 0.72 | [-17.04, 17.95] | 0.53 | 0.53 | 0.52
f_br23~~f_br23 | 0.15 | [0.10, 0.21] | 1.00 | 1.00 | 0.00
f_c30~~f_c30 | 0.08 | [0.02, 0.13] | 1.00 | 0.85 | 0.00
s_br23~~s_br23 | 0.20 | [0.14, 0.28] | 1.00 | 1.00 | 0.02
s_c30~~s_c30 | 0.08 | [4.64e-07, 0.13] | 1.00 | 0.72 | 0.00
comorb~~comorb | 0.23 | [0.16, 0.31] | 1.00 | 1.00 | 0.06
estadio_avz~~estadio_avz | 0.20 | [0.03, 0.31] | 1.00 | 0.95 | 0.02
her2_nega~~her2_nega | 0.25 | [0.17, 0.35] | 1.00 | 1.00 | 0.13
cv_gral~~cv_gral | 0.44 | [0.26, 0.67] | 1.00 | 1.00 | 0.94
salud~~salud | 1.58 | [1.12, 2.21] | 1.00 | 1.00 | 1.00
funcionalidad~~funcionalidad | 8.47e-03 | [2.43e-09, 0.05] | 1.00 | 0.06 | 0.00
sintomas~~sintomas | 0.09 | [3.11e-05, 0.17] | 1.00 | 0.80 | 0.00
biologicas~~biologicas | 4.31e-04 | [1.02e-10, 3.90e-03] | 1.00 | 0.00 | 0.00
f_br23~1 | 2.34 | [2.20, 2.48] | 1.00 | 1.00 | 1.00
f_c30~1 | 2.43 | [2.27, 2.61] | 1.00 | 1.00 | 1.00
s_br23~1 | 1.77 | [1.65, 1.90] | 1.00 | 1.00 | 1.00
s_c30~1 | 2.17 | [1.98, 2.34] | 1.00 | 1.00 | 1.00
comorb~1 | 0.34 | [0.24, 0.45] | 1.00 | 1.00 | 0.76
estadio_avz~1 | 0.34 | [0.24, 0.45] | 1.00 | 1.00 | 0.76
her2_nega~1 | 0.56 | [0.45, 0.67] | 1.00 | 1.00 | 1.00
cv_gral~1 | 0.81 | [0.20, 1.39] | 1.00 | 1.00 | 0.96
salud~1 | 4.33 | [3.94, 4.75] | 1.00 | 1.00 | 1.00