LGB Generations Study

My data is from a study on LGB people in the United States. The researchers investigated many different health factors, well being factors, and centrality of racial and queer identities. They also gathered participants into age groups to examine generational differences. This large dataset can be helpful in understanding what life is like for LGB people in the US, and what factors influence their lives. I will be questioning:

The following plots help illuminate some of the relationships I will be exploring:

 LGBdata <- read.delim("/Users/oliviabrady/Desktop/LGBdata/DS0001/37166-0001-Data.tsv")

This graphic shows the discimination people face within genders (male, female, nonbinary, and NA) and cohort (younger, middle, and older). It seems that young adults face the most discrimination among the cohorts, and nonbinary people tend to face the most discrimination within cohorts, and men the least.

ggplot(LGBdata, aes(as.factor(W1Q28), W1EVERYDAY, fill = as.factor(W1Q28))) +
  geom_boxplot() +
  facet_wrap(~as.factor(COHORT)) +
  xlab("Gender and Cohort") +
  ylab("Everyday Discrimination") +
  ggtitle("Everyday Discrimination in Genders and Cohorts")

This graph shows that internalized homophobia tends to be pretty low in general, but the youngest cohort has the most internalized homophobia.

ggplot(LGBdata, aes(as.factor(COHORT), W1INTERNALIZED, fill = as.factor(COHORT))) +
  geom_boxplot() + 
  xlab("Cohort") +
  ylab("Internalized Homophobia") +
  ggtitle("Internalized Homophobia within Cohorts")

Since the youngest cohort faces the most discrimination, and has the most internalized homophobia, it’s possible there is a relationship between these variables. There seems to be a slight positive correlation here.

ggplot(LGBdata, aes(W1EVERYDAY, W1INTERNALIZED, color = as.factor(COHORT))) +
  geom_point(position = "jitter") +
  xlab("Discimination") +
  ylab("Interalized Homophobia") +
  ggtitle("Discrimination and Internalized Homophobia")