Publications by Philipp Chapkovski, HSE-Moscow
d2d_ukr
Cleaning data merge all d2d obs together: 1.1 keeping only full obs (those who reported for all 11 days) 1.2. dropping duplicates (taking the last one if more than one obs per ID) 1.3. merging: d2d, new year, final survey keep only id, 3 main dv, experience expanded collapsing on id, calculating: average per each dv, count of each experience type ...
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Speak Up or Stay Silent: How Revealing War Positions Affects Affective Polarization in Russia
Table of Contents Clean data Show balance table Comparative differences between different decisions towards opposite party Comparative differencees between those who decided to hide, was hidden, and just open oppsoition Regression table for those whose position was shown to a dictator separate for those who did not reveal Reveal project analysis ...
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IRT analysis
Table of Contents Some descriptives: Mean sending values per city Mean return values per city let’s melt the data on sender_decision_ let’ build a chart showing for each city involved average sending decisions to away city, home city, and difference between them let’s analyse sender and return decision by target cities some fixed effects mod...
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time analysis Author Chapkovski, Peer, Brandt Overall number of participants per local hour of the day `geom_smooth()` using method = 'loess' and formula = 'y ~ x' First half of the day vs second half of the day analysis Let’s split it by the median local hour, produce the binary variable dividing the population in two halfs and check wheth...
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Untitled Quarto graph LR A[Start] --> B{Decision} B -->|Yes| C[Do Something] B -->|No| D[Do Something Else] C --> E[End] D --> E let’s build a timeline in mermaid gantt title A Gantt Diagram dateFormat YYYY-MM-DD section Section A task :a1, 2022-01-01, 30d Another task :after a1 , 20d ...
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time of the day analysis Author Peer, Brandt, Chapkovski Getting libraries library(pacman) p_load(tidyverse, lubridate, readr, ggplot2, scales, lutz,jsonlite, glue, ggpubr, kableExtra) Time of the day analysis local_folder='/Users/chapkovski/Documents/peer_brandt_paper/' fn<-glue('{local_folder}full_data.csv') data<-read_csv(fn) %>% mutat...
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first steps with tail project loading libraries # let's use cache library(pacman) p_load(tidyverse, fixest, gtsummary, lme4, lmtest, sandwich, sjPlot) Reading in data setwd("/Users/chapkovski/Downloads/Data Backup 2/RemadeDump") fileNames<-list.files(path = ".", pattern = "all*") raw_df <- do.call(rbind, lapply(fileNames, function(x) read.csv...
849 sym Python (6575 sym/11 pcs) 5 tbl
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first steps with tail project loading libraries library(pacman) p_load(tidyverse, fixest, gtsummary, lme4, lmtest, sandwich, sjPlot) Reading in data setwd("/Users/chapkovski/Downloads/Data Backup 2/RemadeDump") fileNames<-list.files(path = ".", pattern = "all*") raw_df <- do.call(rbind, lapply(fileNames, function(x) read.csv(file=x) ) ) Clean...
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# one participant managed to participate twice. therefore we drop him/her entirely. sneaky_guy <- '63d196c147d1f420690e5b87' risk_fn<-'/Users/chapkovski/Documents/umbrella_analysis/Data/raw_data/Study 5/umbrella_2023-10-18.csv' q_fn<-'/Users/chapkovski/Documents/umbrella_analysis/Data/raw_data/Study 5/q_2023-10-18.csv' risk_df<-read_csv(risk_fn) %...
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Getting necessary libraries Reading and cleaning data #add sample variable Toloka$sample <- "Toloka" Prolific$sample <- "Prolific" CR$sample <- "CR" Mturk$sample <- "MTurk" Connect$sample <- "Connect" Besample$sample <- "Besample" #combine data files raw.data <- bind_rows(Toloka, Prolific, CR, Mturk, Connect, Besample) #filter data for finished...
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