Publications by Ismael calandri
covid metanalisis 2
Part 0 data correction knitr::opts_chunk$set(echo = T) library(estmeansd) # BoxCox estimacion del grupo expuesto Raman,2020 bc.mean.sd(q1.val=25,med.val=27,q3.val=29,n=59) ## $est.mean ## [1] 27.0777 ## ## $est.sd ## [1] 3.090902 # BoxCoxestimacion del grupo no expuesto Raman,2020 bc.mean.sd(q1.val=27,med.val=28,q3.val=29,n=30) ## $est...
2105 sym R (2333 sym/10 pcs) 3 img
Meta-covid
Part 0 data correction knitr::opts_chunk$set(echo = T) library(estmeansd) # BoxCox estimacion del grupo expuesto Raman,2020 bc.mean.sd(q1.val=25,med.val=27,q3.val=29,n=19) ## $est.mean ## [1] 26.93041 ## ## $est.sd ## [1] 3.214925 # BoxCoxestimacion del grupo no expuesto Raman,2020 bc.mean.sd(q1.val=27,med.val=28,q3.val=29,n=30) ## $es...
2285 sym R (5089 sym/15 pcs) 4 img
FTDkst
## ## Attaching package: 'table1' ## The following objects are masked from 'package:base': ## ## units, units<- ## Install package "strengejacke" from GitHub (`devtools::install_github("strengejacke/strengejacke")`) to load all sj-packages at once! Tabla1 Overall(N=134) Edad Mean (SD) 42.9 (12.5) Median [Min, Max] 39.0 [25.0, 77.0] ...
83 sym R (120834 sym/8 pcs) 2 tbl
validacion FTDKS
## ## Attaching package: 'table1' ## The following objects are masked from 'package:base': ## ## units, units<- Tabla1 Overall(N=134) Edad Mean (SD) 42.9 (12.5) Median [Min, Max] 39.0 [25.0, 77.0] Sexo Female 78 (58.2%) Male 56 (41.8%) Education_lvl Fellow program 12 (9.0%) Fellow Program 3 (2.2%) Master in medicine 17 (12.7%...
78 sym R (120543 sym/3 pcs) 2 tbl
cogvid5_6
Table 1. Demographics Characteristic Healthy control, N = 451 Covid, N = 451 p-value2 Age (y) 57 (46, 64) 50 (43, 63) 0.4 sex 0.7 Male 25 (56%) 23 (51%) Female 20 (44%) 22 (49%) Education (y) 17.00 (15.00, 18.00) 17.00 (15.00, 18.00) >0.9 CAIDE dementia score 6.00 (3.00, 7.00) 5.00 (2.00, 7.00) 0.3 1 Median (IQR); n (%) 2 ...
964 sym R (1607 sym/1 pcs) 6 img 9 tbl
covid_draft
##############################Data wrangling section########################################## ##Data tidy library(tidyverse) base<-base %>% rename( Diagnosis = dx, Symptomatic = covid_sint, Hospitalization = hospitalizacion, ICU =terapia, ICU_days = dias_terapia, s_Anosmia = covid_symptoms___0, s_Ageus...
1855 sym R (31414 sym/27 pcs) 7 img 7 tbl
CogVid casos y controles2
Table 1. Demographics Esta tabla, y la siguiente, las pense para mostrar la poblacion. Ya que es en definitiva una serie de casos, es muy importante mostrar como son los casos por eso la tabla 2 Characteristic Healthy control, N = 361 Covid, N = 361 p-value2 Age (y) 58 (48, 64) 51 (44, 65) 0.7 sex >0.9 Male 18 (50%) 18 (50%) Female 18 (50%)...
1825 sym 4 img 7 tbl
Document
Delay to consultation Survival analysis Time to death ## Warning in .pvalue(fit, data = data, method = method, pval = pval, pval.coord = pval.coord, : There are no survival curves to be compared. ## This is a null model. Time to death by diagnosis Time to nursing home admission ## Warning in .pvalue(fit, data = data, method = method, pval ...
186 sym R (338 sym/2 pcs) 8 img
CogVid casos y controles
Table 1. Demographics Esta tabla, y la siguiente, las pense para mostrar la poblacion. Ya que es en definitiva una serie de casos, es muy importante mostrar como son los casos por eso la tabla 2 Characteristic Healthy control, N = 361 Covid, N = 361 p-value2 Age (y) 58 (48, 64) 51 (44, 65) 0.7 sex >0.9 Male 18 (50%) 18 (50%) Female 18 (50%)...
1756 sym 4 img 7 tbl
CogVid
Demographics Characteristic Healthy control, N = 361 Covid, N = 361 p-value2 Age (y) 58 (48, 64) 51 (44, 65) 0.7 sex >0.9 Male 18 (50%) 18 (50%) Female 18 (50%) 18 (50%) escolaridad 18.00 (15.00, 18.00) 18.00 (15.00, 18.00) 0.9 total_caide 6.00 (5.00, 7.00) 5.00 (3.00, 7.00) 0.2 1 Median (IQR); n (%) 2 Wilcoxon ra...
203 sym 3 tbl