senzaki

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library(tidyverse)

## ── Attaching packages ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.3.0 ──

## ✓ ggplot2 3.2.1     ✓ purrr   0.3.3
## ✓ tibble  2.1.3     ✓ dplyr   0.8.5
## ✓ tidyr   1.0.2     ✓ stringr 1.4.0
## ✓ readr   1.3.1     ✓ forcats 0.4.0

## ── Conflicts ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

library(gridExtra)

## 
## Attaching package: 'gridExtra'

## The following object is masked from 'package:dplyr':
## 
##     combine

d <- read.csv("/Users/caoanjie/Desktop/senzaki.csv")
d

d %>%  mutate(S1_imada_coding = S1_ChildOnly_Back - S1_ChildOnly_Focal,
             S1_koster_coding = S1_ChildOnly_Focal / (S1_ChildOnly_Back + S1_ChildOnly_Focal)) %>% 
  filter(!is.na(S1_imada_coding) & !is.na(S1_koster_coding)) -> d_new_score 

d_new_score %>% 
  select(Pp., Culture, AgeGroup, S1_imada_coding, S1_koster_coding) %>% 
  gather(scoring_scheme, score, S1_imada_coding:S1_koster_coding) %>% 
  group_by(Culture, scoring_scheme) %>% 
  summarize(mean = mean(score),
            sd = sd(score),
            n = n()) %>%
    mutate(ci_range_95 =  1.96 * (sd/sqrt(n)),
         ci_lower = mean - ci_range_95,
         ci_upper = mean + ci_range_95) -> d_summary
 
d_summary

d_summary %>% filter(scoring_scheme == "S1_imada_coding") %>% 
  ggplot(aes(x = (as.factor(Culture)), y = mean)) + 
  facet_wrap(~scoring_scheme, ncol = 2) +
  geom_point() + 
  geom_pointrange(aes(ymin = ci_lower, ymax = ci_upper)) +
  ylim(-2, 5) -> p1

d_summary %>% filter(scoring_scheme == "S1_koster_coding") %>% 
  ggplot(aes(x = (as.factor(Culture)), y = mean)) + 
  facet_wrap(~scoring_scheme, ncol = 2) +
  geom_point()+ 
  geom_pointrange(aes(ymin = ci_lower, ymax = ci_upper)) -> p2

d_summary %>% filter(scoring_scheme == "S1_koster_coding") %>% 
  ggplot(aes(x = (as.factor(Culture)), y = mean)) + 
  facet_wrap(~scoring_scheme, ncol = 2) +
  geom_point()+ 
  ylim(-2,5) + 
  labs(title = "same scale as s1") +
  geom_pointrange(aes(ymin = ci_lower, ymax = ci_upper)) -> p3

grid.arrange(p1, p2, p3, nrow = 1)

d_new_score %>% ggplot(aes(x = S1_ChildOnly_Focal, y = S1_imada_coding)) + geom_point()

d_new_score %>% ggplot(aes(x = S1_ChildOnly_Focal, y = S1_koster_coding)) + geom_point()

d_new_score %>% ggplot(aes(x = S1_imada_coding, y = S1_koster_coding)) + geom_point()