## 
## Use 'expss_output_rnotebook()' to display tables inside R Notebooks.
##  To return to the console output, use 'expss_output_default()'.
## 
## Attaching package: 'expss'
## The following objects are masked from 'package:dplyr':
## 
##     between, compute, contains, first, last, na_if, recode, vars

Prevalence metanalysis

Outliers and influential analysis

## Identified outliers (fixed-effect model) 
## ---------------------------------------- 
## "Romoli, 2020", "Oliveira, 2020", "Moon, 2016" 
##  
## Results with outliers removed 
## ----------------------------- 
##                   proportion           95%-CI %W(fixed) %W(random) exclude
## Dong Ah Lee, 2021     0.1250 [0.0641; 0.2127]       4.1        7.7        
## Romoli, 2020          0.0743 [0.0534; 0.1002]       0.0        0.0       *
## Tynas, 2020           0.1613 [0.0932; 0.2520]       4.3        8.0        
## Morris, 2020          0.1370 [0.1167; 0.1593]      48.0       18.7        
## Oliveira, 2020        0.2714 [0.1720; 0.3910]       0.0        0.0       *
## Alessandro, 2019      0.0788 [0.0457; 0.1248]       9.4       12.1        
## Himeno, 2017          0.0667 [0.0337; 0.1162]       7.6       11.0        
## Arena, 2017           0.1403 [0.0973; 0.1932]      10.2       12.5        
## Moon, 2016            0.3333 [0.1459; 0.5697]       0.0        0.0       *
## Kwon, 2014            0.1176 [0.0712; 0.1795]       7.1       10.6        
## Auyeung, 2011         0.1852 [0.0630; 0.3808]       1.3        3.2        
## Lampl, 2004           0.1875 [0.0405; 0.4565]       0.8        2.0        
## Agosti, 2006          0.1412 [0.0751; 0.2336]       3.9        7.5        
## Hinge, 1986           0.2162 [0.1289; 0.3272]       3.4        6.9        
## 
## Number of studies combined: k = 11
## 
##                      proportion           95%-CI
## Fixed effect model       0.1236 [0.1096; 0.1382]
## Random effects model     0.1241 [0.1005; 0.1496]
## 
## Quantifying heterogeneity:
##  tau^2 = 0.0016 [0.0000; 0.0105]; tau = 0.0396 [0.0000; 0.1026]
##  I^2 = 50.0% [0.3%; 75.0%]; H = 1.41 [1.00; 2.00]
## 
## Test of heterogeneity:
##      Q d.f. p-value
##  20.01   10  0.0292
## 
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Freeman-Tukey double arcsine transformation
## - Clopper-Pearson confidence interval for individual studies
## 
## Identified outliers (random-effects model) 
## ------------------------------------------ 
## "Romoli, 2020", "Oliveira, 2020" 
##  
## Results with outliers removed 
## ----------------------------- 
##                   proportion           95%-CI %W(fixed) %W(random) exclude
## Dong Ah Lee, 2021     0.1250 [0.0641; 0.2127]       4.0        7.9        
## Romoli, 2020          0.0743 [0.0534; 0.1002]       0.0        0.0       *
## Tynas, 2020           0.1613 [0.0932; 0.2520]       4.3        8.1        
## Morris, 2020          0.1370 [0.1167; 0.1593]      47.6       16.1        
## Oliveira, 2020        0.2714 [0.1720; 0.3910]       0.0        0.0       *
## Alessandro, 2019      0.0788 [0.0457; 0.1248]       9.3       11.5        
## Himeno, 2017          0.0667 [0.0337; 0.1162]       7.5       10.6        
## Arena, 2017           0.1403 [0.0973; 0.1932]      10.1       11.8        
## Moon, 2016            0.3333 [0.1459; 0.5697]       1.0        2.9        
## Kwon, 2014            0.1176 [0.0712; 0.1795]       7.0       10.3        
## Auyeung, 2011         0.1852 [0.0630; 0.3808]       1.3        3.5        
## Lampl, 2004           0.1875 [0.0405; 0.4565]       0.8        2.3        
## Agosti, 2006          0.1412 [0.0751; 0.2336]       3.9        7.7        
## Hinge, 1986           0.2162 [0.1289; 0.3272]       3.4        7.1        
## 
## Number of studies combined: k = 12
## 
##                      proportion           95%-CI
## Fixed effect model       0.1253 [0.1113; 0.1400]
## Random effects model     0.1302 [0.1040; 0.1586]
## 
## Quantifying heterogeneity:
##  tau^2 = 0.0022 [0.0002; 0.0160]; tau = 0.0474 [0.0135; 0.1266]
##  I^2 = 56.9% [18.0%; 77.4%]; H = 1.52 [1.10; 2.10]
## 
## Test of heterogeneity:
##      Q d.f. p-value
##  25.55   11  0.0076
## 
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Freeman-Tukey double arcsine transformation
## - Clopper-Pearson confidence interval for individual studies
## [===========================================================================] DONE

## Eggers' test of the intercept 
## ============================= 
## 
##  intercept       95% CI    t        p
##      1.598 -0.28 - 3.47 1.67 0.120869
## 
## Eggers' test does not indicate the presence of funnel plot asymmetry.

Risk factors prevalence

Female sex

Hypertension

## Dyslipidemia

Smoking

Diabetes

Stroke

Coronary artery disease

Atrial fibrillation

DWI lesions

## Warning in metabin(data$`DWI_eventos en exp`, data$`DWI_numero de expuestos`, :
## Studies with non-positive values for n.e and / or n.c get no weight in meta-
## analysis.

reflux

EEG

## Warning in metabin(data$`EEG_eventos en exp`, data$`EEG_numero de expuestos`, :
## Studies with non-positive values for n.e and / or n.c get no weight in meta-
## analysis.