Relationship Duration

Datawrangling

Data and Functions

source("0_helpers.R")
load("data/cleaned_selected_wrangled.rdata")

Wrangle data

Relationship duration

Linear relationship duration

qplot(data$relationship_duration)

Factor1 relationship duration

Divide relationship duration into quartiles

data = data %>%
   mutate(relationship_duration_factor_quartiles = 
            factor(ifelse(relationship_status == "Single",
                   "Single",
                   ifelse(relationship_duration <= 12,
                          "upto12months",
                          ifelse(relationship_duration <= 28, 
                                 "upto28months",
                                 ifelse(relationship_duration <= 52,
                                        "upto52months",
                                        ifelse(relationship_duration > 52,
                                        "morethan52months",
                                        NA))))),
                   levels = c("Single", "upto12months",
                              "upto28months", "upto52months",
                              "morethan52months")))


data %>% 
  group_by(relationship_duration_factor_quartiles) %>%
  summarise(count = n()) %>%
  add_column(duration_in_years = c("Single",
                                   "upto1year",
                                   "upto2.3years",
                                   "upto4.3years",
                                   "morethan4.3years")) %>%
  select(relationship_duration_factor_quartiles, duration_in_years, count) %>%
  kable()

relationship_duration_factor_quartiles	duration_in_years	count
Single	Single	405
upto12months	upto1year	198
upto28months	upto2.3years	198
upto52months	upto4.3years	188
morethan52months	morethan4.3years	190

qplot(data$relationship_duration_factor_quartiles)

plot = ggplot(data, aes(relationship_duration)) +
  geom_histogram(aes(fill = relationship_duration_factor_quartiles), bins = 300) +
  labs(x = "Relationship Duration (in months)",
       y = "Count") + 
  scale_x_continuous(breaks = c(c(0:30) * 12),
                     labels = c(c(0:30) * 12)) +
  apatheme +
  #theme(legend.position = "bottom") +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) +
  scale_fill_manual(name = "Categories\nRelationship\nDuration",
                    labels = c("0‒12 months",
                                 "13‒28 months",
                                 "29‒52 months",
                                 "> 52 months"),
                    values = c("#1B9E77", "#7570B3", "#D95F02", "#E7298A"))

jpeg('Relationship Duration.jpg', 
     width = 700, height = 500, quality = 100)
plot
dev.off()

## png 
##   2

Factor2 relationship duration

Divide relationship duration into 8 quantiles

quantiles = quantile(as.numeric(data$relationship_duration),
                     na.rm = T,
                     probs = c(0, 0.125, 0.25, 0.375, 0.5,0.625, 0.75, 0.875, 1))

data = data %>%
  mutate(relationship_duration_factor_finegrained = 
           factor(ifelse(relationship_status == "Single",
                  "Single",
                  ifelse(relationship_duration <= quantiles[2],
                         "upto6months",
                         ifelse(relationship_duration <= quantiles[3],
                                "upto12months",
                                ifelse(relationship_duration <= quantiles[4],
                                       "upto20months",
                                       ifelse(relationship_duration <= quantiles[5],
                                              "upto28months",
           ifelse(relationship_duration <= quantiles[6],
                  "upto38months",
                  ifelse(relationship_duration <= quantiles[7],
                         "upto52months",
                         ifelse(relationship_duration <= quantiles[8],
                                "upto85months",
                                ifelse(relationship_duration > quantiles[8],
                                       "morethan85months",
                                       NA))))))))),
           levels = c("Single", "upto6months", "upto12months",
                      "upto20months", "upto28months",
                      "upto38months", "upto52months",
                      "upto85months", "morethan85months")))

data %>% 
  group_by(relationship_duration_factor_finegrained) %>%
  summarise(count = n()) %>%
  add_column(duration_in_years = c("Single",
                                   "upto0.5years",
                                   "upto1year",
                                   "upto1.7year",
                                   "upto2.3years",
                                   "upto3.2years",
                                   "upto4.3years",
                                   "upto7.1years",
                                   "morethan7.1years")) %>%
  select(relationship_duration_factor_finegrained, duration_in_years, count)  %>%
  kable()

relationship_duration_factor_finegrained	duration_in_years	count
Single	Single	405
upto6months	upto0.5years	120
upto12months	upto1year	78
upto20months	upto1.7year	98
upto28months	upto2.3years	100
upto38months	upto3.2years	96
upto52months	upto4.3years	92
upto85months	upto7.1years	93
morethan85months	morethan7.1years	97

qplot(data$relationship_duration_factor_finegrained) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))

ggplot(data, aes(relationship_duration)) +
  geom_histogram(aes(fill = relationship_duration_factor_finegrained), bins = 200) +
  theme(legend.title = element_blank(), legend.position = "bottom")

Factor3 relationship duration

https://sci-hub.st/10.1016/j.ssresearch.2015.01.009 Effects of relationship duration, cohabitation, and marriage on the frequency of intercourse in couples: Findings from German panel data

Relationship Duration * 0-5 months * 6-11 months * 1-2 years * 2-3 years * 3-4 years * 4-5 years * 5-6 years * 6-8 years * 8-10 years * 10-12 years * 12-14 years * 14-16 years * > 16 years

data = data %>%
  mutate(relationship_duration_factor_schroeder = 
           factor(ifelse(relationship_status == "Single",
                  "Single",
                  ifelse(relationship_duration < 6,
                         "0to5months",
                         ifelse(relationship_duration < 12,
                                "6to11months",
                                ifelse(relationship_duration <= 24,
                                       "1to2years",
                                       ifelse(relationship_duration <= 36,
                                              "2to3years",
           ifelse(relationship_duration <= 48,
                  "3to4years",
                  ifelse(relationship_duration <= 60,
                         "4to5years",
                         ifelse(relationship_duration <= 72,
                                "5to6years",
                                ifelse(relationship_duration <= 96,
                                       "6to8years",
                                       ifelse(relationship_duration <= 120,
                                              "8to10years",
           ifelse(relationship_duration > 120, "morethan10years",
                  NA))))))))))),
           levels = c("Single", "0to5months", "6to11months",
                      "1to2years", "2to3years",
                      "3to4years", "4to5years",
                      "5to6years", "6to8years",
                      "8to10years", "morethan10years")))

data %>% 
  group_by(relationship_duration_factor_schroeder) %>%
  summarise(count = n()) %>%
  kable()

relationship_duration_factor_schroeder	count
Single	405
0to5months	92
6to11months	88
1to2years	160
2to3years	125
3to4years	93
4to5years	52
5to6years	44
6to8years	47
8to10years	25
morethan10years	48

qplot(data$relationship_duration_factor_schroeder) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))

ggplot(data, aes(relationship_duration)) +
  geom_histogram(aes(fill = relationship_duration_factor_schroeder), bins = 200) +
  theme(legend.title = element_blank(), legend.position = "bottom")

Plots

ggplot(data, aes(relationship_duration_factor_finegrained, diary_libido_mean)) +
  geom_jitter() +
  stat_summary(fun.data=mean_cl_normal, geom="pointrange", color="red")

ggplot(data, aes(relationship_duration_factor_finegrained, diary_sex_active_sex_mean)) +
  geom_jitter() +
  stat_summary(fun.data=mean_cl_normal, geom="pointrange", color="red")

ggplot(data, aes(relationship_duration_factor_finegrained, partner_attractiveness_body)) +
  geom_jitter() +
  stat_summary(fun.data=mean_cl_normal, geom="pointrange", color="red")

ggplot(data, aes(relationship_duration_factor_finegrained, relationship_satisfaction_overall)) +
  geom_jitter() +
  stat_summary(fun.data=mean_cl_normal, geom="pointrange", color="red")

ggplot(data, aes(relationship_duration_factor_finegrained, satisfaction_sexual_intercourse)) +
  geom_jitter() +
  stat_summary(fun.data=mean_cl_normal, geom="pointrange", color="red")