##read in data
#load package
#install.packages("tinytex")
library(psych)
library(knitr)
library(tidyverse)## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──## ✓ ggplot2 3.3.5 ✓ purrr 0.3.4
## ✓ tibble 3.1.6 ✓ dplyr 1.0.7
## ✓ tidyr 1.1.4 ✓ stringr 1.4.0
## ✓ readr 2.0.2 ✓ forcats 0.5.1## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x ggplot2::%+%() masks psych::%+%()
## x ggplot2::alpha() masks psych::alpha()
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(tinytex)
LTCC <- read.csv("LTCCdata.csv")#Create ShoCCS composites
#composite for cr short
LTCC$c_ref_S <- with(data = LTCC, (cr_3.t1 + cr_6.t1 + cr_7.t1 + cr_8.t1) / 4)
#composite for cm short
LTCC$c_mot_S <- with(data = LTCC, (cm_2.t1 + cm_5.t1 + cm_7.t1 + cm_8.t1) / 4)
#composite for ca short
LTCC$c_act_S <- with(data = LTCC, (ca_1.t1 + ca_2.t1 + ca_4.t1 + ca_5.t1 + ca_9.t1) / 5)#Examine the gender breakdown of the sample by YO or YLC
table(LTCC$gender.t1, LTCC$DSET) %>% kable()| 0 | 1 | |
|---|---|---|
| 0 | 102 | 173 |
| 1 | 61 | 79 |
| 2 | 2 | 6 |
| 4 | 2 | 7 |
# 0 = girl; 1 = boy; 2 = I want to describe; 4 = I don't want to answer
#For DSET: 0 = YLC and 1 = YO#Examine the racial breakdown of the sample by YO or YLC
table(LTCC$d_self.t1, LTCC$DSET) %>% kable()| 0 | 1 | |
|---|---|---|
| 0 | 30 | 27 |
| 1 | 50 | 52 |
| 2 | 46 | 153 |
| 3 | 24 | 17 |
| 4 | 18 | 14 |
# 0 = Asian/Indian; 1 = Black/African American; 2 = Latino/Hispanic; 3 = two or more races; 4 = White/caucasion#Time in Program Descriptives by YO or YLC
table(LTCC$tip.t1, LTCC$DSET) %>% kable()| 0 | 1 | |
|---|---|---|
| 0 | 10 | 27 |
| 1 | 10 | 35 |
| 2 | 5 | 60 |
| 3 | 104 | 61 |
| 4 | 17 | 41 |
| 5 | 16 | 16 |
| 6 | 6 | 25 |
#"This is my first day." = 0; "A few days" = 1; "A few weeks" = 2; "A few months" = 3; "1 year" = 4;
#"2 years" = 5; "More than 2 years" = 6
describeBy(LTCC$tip.t1, LTCC$DSET, mat = TRUE) %>% kable()| item | group1 | vars | n | mean | sd | median | trimmed | mad | min | max | range | skew | kurtosis | se | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| X11 | 1 | 0 | 1 | 168 | 3.071429 | 1.269501 | 3 | 3.117647 | 0.0000 | 0 | 6 | 6 | -0.3076158 | 1.0241500 | 0.0979442 |
| X12 | 2 | 1 | 1 | 265 | 2.762264 | 1.694490 | 3 | 2.708920 | 1.4826 | 0 | 6 | 6 | 0.2475617 | -0.6314806 | 0.1040917 |
#Descriptives for critical reflection by YO or YLC
describeBy(LTCC$c_ref_S, LTCC$DSET, mat = TRUE) %>% kable()| item | group1 | vars | n | mean | sd | median | trimmed | mad | min | max | range | skew | kurtosis | se | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| X11 | 1 | 0 | 1 | 184 | 4.000000 | 1.440296 | 4.250 | 4.114865 | 1.297275 | 1 | 6 | 5 | -0.6041837 | -0.5103667 | 0.1061801 |
| X12 | 2 | 1 | 1 | 318 | 4.213837 | 1.548974 | 4.625 | 4.379883 | 1.667925 | 1 | 6 | 5 | -0.7510792 | -0.5560536 | 0.0868621 |
#Descriptives for Critical Motivation by YO or YLC
describeBy(LTCC$c_mot_S, LTCC$DSET, mat = TRUE) %>% kable()| item | group1 | vars | n | mean | sd | median | trimmed | mad | min | max | range | skew | kurtosis | se | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| X11 | 1 | 0 | 1 | 182 | 5.383242 | 0.8077025 | 5.75 | 5.525685 | 0.37065 | 1.25 | 6 | 4.75 | -1.991195 | 5.494142 | 0.0598709 |
| X12 | 2 | 1 | 1 | 321 | 5.288162 | 0.8071362 | 5.50 | 5.426070 | 0.74130 | 1.75 | 6 | 4.25 | -1.426113 | 1.950706 | 0.0450499 |
#Descriptives for Critical Action by YO or YLC
describeBy(LTCC$c_act_S, LTCC$DSET, mat = TRUE) %>% kable()| item | group1 | vars | n | mean | sd | median | trimmed | mad | min | max | range | skew | kurtosis | se | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| X11 | 1 | 0 | 1 | 180 | 2.19 | 1.043046 | 1.8 | 2.079167 | 0.88956 | 1 | 5 | 4 | 0.7435757 | -0.4034886 | 0.0777440 |
| X12 | 2 | 1 | 1 | 320 | 2.39 | 1.193987 | 2.2 | 2.293750 | 1.48260 | 1 | 5 | 4 | 0.4267449 | -1.0429388 | 0.0667459 |