library(haven)
lec<-read.csv("LEC.Sex.csv")
Gender <- factor(lec$chsex_d1, levels = 1:2, labels = c("Male", "Female")) #Turning gender into a factor
summary(Gender) #Getting summary of gender
## Male Female
## 111 109
Ethnicity <- factor(lec$cethn_d1, levels = 1:6, labels = c("White", "Black", "Hispanic", "Asian-Oriental", "Mixed", "Other")) #Turning ethnicity into a factor
summary(Ethnicity) #Getting summary of ethnicity
## White Black Hispanic Asian-Oriental Mixed
## 154 35 4 6 21
## Other
## 0
Income <- factor(lec$inc_d1, levels = 1:6, labels = c("Less than $20k", "$20k-40k", "$41k-$60k", "$61k-$80k", "$81k-$100k", "Over $100k")) #Turning income into a factor
summary(Income) #Getting summary of income
## Less than $20k $20k-40k $41k-$60k $61k-$80k $81k-$100k
## 12 25 40 41 35
## Over $100k NA's
## 66 1
mean(lec$cage_d1) #Calculating adolescents' mean age
## [1] 13.67034
lecchi <- subset(lec,select=c(chsex_d1,lc31e_c1)) #Designating columns to run chi-square test on
table(lecchi) #Getting table of adolescents' sex and arguments with parents
## lc31e_c1
## chsex_d1 0 1
## 1 91 18
## 2 82 25
library(naniar)
vis_miss(lecchi) #Looking at missing data
## Warning: `gather_()` was deprecated in tidyr 1.2.0.
## Please use `gather()` instead.
lecchi <- na.omit(lecchi) #Excluding missing data
lecchi$chsex_d1 <- as.factor(lecchi$chsex_d1)
levels(lecchi$chsex_d1) <- list('Male'="1",'Female'="2") #Relabel adolescents' sex to ensure it is treated as a factor, not numerical
lecchi$lc31e_c1 <- as.factor(lecchi$lc31e_c1)
levels(lecchi$lc31e_c1) <- list('Did not experience life event'="0",'Did experience life event'="1") #Relabel adolescents' arguments with parents to ensure it is treated as a factor, not numerical
table(lecchi) #Getting table of adolescents' sex and arguments with parents without missing data
## lc31e_c1
## chsex_d1 Did not experience life event Did experience life event
## Male 91 18
## Female 82 25
chiSquareTable <- table(lecchi) #Saving chi-square table as an object
chiSq <- chisq.test(chiSquareTable) #Running chi-square test
chiSq$statistic #Getting chi-square statistic
## X-squared
## 1.188735
chiSq$p.value #Getting chi-square p-value
## [1] 0.2755849
chiSq$residuals #Getting chi-square residuals
## lc31e_c1
## chsex_d1 Did not experience life event Did experience life event
## Male 0.3958983 -0.7940949
## Female -0.3995811 0.8014820
library(rcompanion)
cramerV(chiSquareTable) #Getting chi-square Cramer's V value
## Cramer V
## 0.08578
library(ggplot2)
ggplot(data = lecchi, aes(x = lc31e_c1)) +
geom_bar(aes(fill = chsex_d1),position="dodge") +
xlab("Increased Arguing with Parents") +
ylab("Frequency") +
scale_fill_manual("Adolescent Sex", values = c(
"Male" = "green3", "Female" = "red")) #Creating chi-square bar graph
sessionInfo()
## R version 4.2.1 (2022-06-23)
## Platform: aarch64-apple-darwin20 (64-bit)
## Running under: macOS Monterey 12.6
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] ggplot2_3.3.6 rcompanion_2.4.18 naniar_0.6.1 haven_2.5.1
##
## loaded via a namespace (and not attached):
## [1] httr_1.4.4 sass_0.4.2 tidyr_1.2.1 jsonlite_1.8.0
## [5] splines_4.2.1 bslib_0.4.0 assertthat_0.2.1 expm_0.999-6
## [9] gld_2.6.5 lmom_2.9 highr_0.9 stats4_4.2.1
## [13] coin_1.4-2 cellranger_1.1.0 yaml_2.3.5 pillar_1.8.1
## [17] lattice_0.20-45 glue_1.6.2 visdat_0.5.3 digest_0.6.29
## [21] sandwich_3.0-2 colorspace_2.0-3 plyr_1.8.7 htmltools_0.5.3
## [25] Matrix_1.4-1 pkgconfig_2.0.3 purrr_0.3.4 mvtnorm_1.1-3
## [29] scales_1.2.1 rootSolve_1.8.2.3 tibble_3.1.8 proxy_0.4-27
## [33] generics_0.1.3 farver_2.1.1 ellipsis_0.3.2 withr_2.5.0
## [37] TH.data_1.1-1 cachem_1.0.6 cli_3.4.0 survival_3.3-1
## [41] magrittr_2.0.3 readxl_1.4.1 evaluate_0.16 fansi_1.0.3
## [45] MASS_7.3-57 forcats_0.5.2 class_7.3-20 tools_4.2.1
## [49] data.table_1.14.2 hms_1.1.2 multcomp_1.4-20 lifecycle_1.0.2
## [53] matrixStats_0.62.0 stringr_1.4.1 Exact_3.2 munsell_0.5.0
## [57] compiler_4.2.1 jquerylib_0.1.4 e1071_1.7-11 multcompView_0.1-8
## [61] rlang_1.0.5 grid_4.2.1 rstudioapi_0.14 labeling_0.4.2
## [65] rmarkdown_2.16 boot_1.3-28 DescTools_0.99.46 codetools_0.2-18
## [69] gtable_0.3.1 DBI_1.1.3 R6_2.5.1 zoo_1.8-11
## [73] knitr_1.40 dplyr_1.0.10 fastmap_1.1.0 utf8_1.2.2
## [77] nortest_1.0-4 libcoin_1.0-9 modeltools_0.2-23 stringi_1.7.8
## [81] parallel_4.2.1 Rcpp_1.0.9 vctrs_0.4.1 lmtest_0.9-40
## [85] tidyselect_1.1.2 xfun_0.33
citation("haven")
##
## To cite package 'haven' in publications use:
##
## Wickham H, Miller E, Smith D (2022). _haven: Import and Export
## 'SPSS', 'Stata' and 'SAS' Files_. R package version 2.5.1,
## <https://CRAN.R-project.org/package=haven>.
##
## A BibTeX entry for LaTeX users is
##
## @Manual{,
## title = {haven: Import and Export 'SPSS', 'Stata' and 'SAS' Files},
## author = {Hadley Wickham and Evan Miller and Danny Smith},
## year = {2022},
## note = {R package version 2.5.1},
## url = {https://CRAN.R-project.org/package=haven},
## }
citation("naniar")
##
## To cite package 'naniar' in publications use:
##
## Tierney N, Cook D, McBain M, Fay C (2021). _naniar: Data Structures,
## Summaries, and Visualisations for Missing Data_. R package version
## 0.6.1, <https://CRAN.R-project.org/package=naniar>.
##
## A BibTeX entry for LaTeX users is
##
## @Manual{,
## title = {naniar: Data Structures, Summaries, and Visualisations for Missing Data},
## author = {Nicholas Tierney and Di Cook and Miles McBain and Colin Fay},
## year = {2021},
## note = {R package version 0.6.1},
## url = {https://CRAN.R-project.org/package=naniar},
## }
citation("ggplot2")
##
## To cite ggplot2 in publications, please use:
##
## H. Wickham. ggplot2: Elegant Graphics for Data Analysis.
## Springer-Verlag New York, 2016.
##
## A BibTeX entry for LaTeX users is
##
## @Book{,
## author = {Hadley Wickham},
## title = {ggplot2: Elegant Graphics for Data Analysis},
## publisher = {Springer-Verlag New York},
## year = {2016},
## isbn = {978-3-319-24277-4},
## url = {https://ggplot2.tidyverse.org},
## }
citation("rcompanion") #Getting citations
##
## To cite package 'rcompanion' in publications use:
##
## Mangiafico S (2022). _rcompanion: Functions to Support Extension
## Education Program Evaluation_. R package version 2.4.18,
## <https://CRAN.R-project.org/package=rcompanion>.
##
## A BibTeX entry for LaTeX users is
##
## @Manual{,
## title = {rcompanion: Functions to Support Extension Education Program Evaluation},
## author = {Salvatore Mangiafico},
## year = {2022},
## note = {R package version 2.4.18},
## url = {https://CRAN.R-project.org/package=rcompanion},
## }