Novelty
Jake Rothschild
6/20/2019
rm(list = ls())
setwd("~/Downloads")
library(foreign)
sex_data <- read.spss("sex_data.sav", use.value.label=TRUE, to.data.frame=TRUE)Libraries/themes
library(ggplot2)
library(tidyverse)
library(gridExtra)
library(finalfit)
library(kableExtra)
library(xtable)
jrothsch_theme <- theme_bw() +
theme(text = element_text(size = 10, face = "bold", color = "deepskyblue4"),panel.grid = element_blank(),axis.text = element_text(size = 10, color = "gray13"), axis.title = element_text(size = 10, color = "red"), legend.text = element_text(colour="Black", size=10), legend.title = element_text(colour="Black", size=7), plot.subtitle = element_text(size=14, face="italic", color="black"))Removing obserations without our key variables
sex_data <- sex_data[!is.na(sex_data$status),]
sex_data <- sex_data[!is.na(sex_data$age),]
sex_data <- sex_data[!is.na(sex_data$Years_PrimaryPartner),]
sex_data <- sex_data[!is.na(sex_data$MALE),]
sex_data <- sex_data[!is.na(sex_data$satis24),]
sex_data <- sex_data[!is.na(sex_data$sexfreq),]Distributions of trying new things, by Marriage Status
Raw Numbers
sex_data <- sex_data %>% mutate(freq_num = 7 - as.numeric(sexfreq))
novelty_sum <- sex_data %>%
group_by(satis24, married) %>%
summarize(nobs = n(),
like = mean(totlike),
want = mean(want),
frequency = mean(as.numeric(freq_num)))
ggplot(novelty_sum, aes(x = satis24, y = nobs,fill = as.factor(married))) +
geom_bar(stat = 'identity',position = "dodge") +
geom_text(aes(label = nobs),color = "black", position = position_dodge(width = 1)) +
coord_flip() +
jrothsch_theme +
scale_fill_discrete(labels = c("Unmarried", "Married")) +
labs(title = "Trying New Things, By Marriage Status", x = "Frequency Of Trying New Things", y = "Number Of Participants", fill = "")
As Percentage Of Group Total
novelty_sum <- novelty_sum %>%
group_by(married) %>%
mutate(total_obs_ms = sum(nobs),
obs_as_pct = nobs/total_obs_ms)
ggplot(novelty_sum, aes(x = satis24, y = obs_as_pct,fill = as.factor(married))) +
geom_bar(stat = 'identity',position = "dodge") +
geom_text(aes(label = round(obs_as_pct*100)),color = "black", position = position_dodge(width = 1)) +
coord_flip() +
jrothsch_theme +
scale_fill_discrete(labels = c("Unmarried", "Married")) +
scale_y_continuous(label = scales::percent) +
labs(title = "Rate Of Trying New Things, By Marriage Status", x = "Rate Of Trying New Things", y = "Percent Of Participants", fill = "")
WLF by Trying New things, With Group size
Wanting
ggplot(data = novelty_sum, aes(x = satis24, y = want, size = obs_as_pct)) +
geom_point(aes(color = as.factor(married)), alpha = .5) +
jrothsch_theme +
labs(title = "Sex Wanting By Marriage And Propensity To Try New Things", x = "Trying New Things", y = "Liking", color = "", size = "Percentage Of Category") +
scale_color_discrete(labels = c("Unmarried", "Married")) +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
Liking
ggplot(data = novelty_sum, aes(x = satis24, y = like, size = obs_as_pct)) +
geom_point(aes(color = as.factor(married)), alpha = .5) +
jrothsch_theme +
labs(title = "Sex Liking By Marriage And Propensity To Try New Things", x = "Trying New Things", y = "Liking", color = "", size = "Percentage Of Category") +
scale_color_discrete(labels = c("Unmarried", "Married")) +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
Frequency
ggplot(data = novelty_sum, aes(x = satis24, y = frequency, size = obs_as_pct)) +
geom_point(aes(color = as.factor(married)), alpha = .5) +
jrothsch_theme +
labs(title = "Sex Frequency By Marriage And Propensity To Try New Things", x = "Trying New Things", y = "Liking", color = "", size = "Percentage Of Category") +
scale_color_discrete(labels = c("Unmarried", "Married")) +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
Age/Duration And Trying New Things
Age
agedursum <- sex_data %>%
group_by(satis24) %>%
summarize(age = mean(age),
duration = mean(Years_PrimaryPartner))
ggplot(data = agedursum, aes(x = satis24, y = age)) +
geom_point() +
jrothsch_theme +
labs(title = "Average Age, By Trying New Things", x = "Trying New Things", y = "Age") +
scale_color_discrete(labels = c("Unmarried", "Married")) +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
ggplot(data = agedursum, aes(x = satis24, y = duration)) +
geom_point() +
jrothsch_theme +
labs(title = "Relationship Duration, by Trying New Things", x = "Trying New Things", y = "Duration") +
scale_color_discrete(labels = c("Unmarried", "Married")) +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
Marriage Age Effects
Baseline Marriage Age Effect
want <- ggplot(data = sex_data, aes(x = age, y = want, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Want by Marriage/Age", x = "Age", y = "Want", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
like <- ggplot(data = sex_data, aes(x = age, y = totlike, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Like by Marriage/Age", x = "Age", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
freq <- ggplot(data = sex_data, aes(x = age, y = freq_num, color = as.factor(married))) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Frequency by Marriage/Age", x = "Age", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
grid.arrange(want, like, freq)
Try Always
sex_data_try <- sex_data %>%
filter(satis24 == "Always")
want <- ggplot(data = sex_data_try, aes(x = age, y = want, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Want by Marriage/Age", x = "Age", y = "Want", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
like <- ggplot(data = sex_data_try, aes(x = age, y = totlike, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Like by Marriage/Age", x = "Age", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
freq <- ggplot(data = sex_data_try, aes(x = age, y = freq_num, color = as.factor(married))) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Frequency by Marriage/Age", x = "Age", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
grid.arrange(want, like, freq)
Try Often
sex_data_try <- sex_data %>%
filter(satis24 == "Often or most of the time")
want <- ggplot(data = sex_data_try, aes(x = age, y = want, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Want by Marriage/Age", x = "Age", y = "Want", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
like <- ggplot(data = sex_data_try, aes(x = age, y = totlike, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Like by Marriage/Age", x = "Age", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
freq <- ggplot(data = sex_data_try, aes(x = age, y = freq_num, color = as.factor(married))) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Frequency by Marriage/Age", x = "Age", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
grid.arrange(want, like, freq)
Try Sometimes
sex_data_try <- sex_data %>%
filter(satis24 == "Moderate amount of the time")
want <- ggplot(data = sex_data_try, aes(x = age, y = want, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Want by Marriage/Age", x = "Age", y = "Want", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
like <- ggplot(data = sex_data_try, aes(x = age, y = totlike, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Like by Marriage/Age", x = "Age", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
freq <- ggplot(data = sex_data_try, aes(x = age, y = freq_num, color = as.factor(married))) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Frequency by Marriage/Age", x = "Age", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
grid.arrange(want, like, freq)
Try Occasionally
sex_data_try <- sex_data %>%
filter(satis24 == "Occasionally or some of the time")
want <- ggplot(data = sex_data_try, aes(x = age, y = want, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Want by Marriage/Age", x = "Age", y = "Want", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
like <- ggplot(data = sex_data_try, aes(x = age, y = totlike, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Like by Marriage/Age", x = "Age", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
freq <- ggplot(data = sex_data_try, aes(x = age, y = freq_num, color = as.factor(married))) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Frequency by Marriage/Age", x = "Age", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
grid.arrange(want, like, freq)
Try Never
sex_data_try <- sex_data %>%
filter(satis24 == "Never")
want <- ggplot(data = sex_data_try, aes(x = age, y = want, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Want by Marriage/Age", x = "Age", y = "Want", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
like <- ggplot(data = sex_data_try, aes(x = age, y = totlike, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Like by Marriage/Age", x = "Age", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
freq <- ggplot(data = sex_data_try, aes(x = age, y = freq_num, color = as.factor(married))) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Frequency by Marriage/Age", x = "Age", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
grid.arrange(want, like, freq)
Marriage Duration Effects
Baseline Marriage Duration Effect
sex_data <- sex_data %>%
filter(Years_PrimaryPartner < 50)
want <- ggplot(data = sex_data, aes(x = Years_PrimaryPartner, y = want, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Want by Marriage/Duration", x = "Duration", y = "Want", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
like <- ggplot(data = sex_data, aes(x = Years_PrimaryPartner, y = totlike, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Like by Marriage/Duration", x = "Duration", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
freq <- ggplot(data = sex_data, aes(x = Years_PrimaryPartner, y = freq_num, color = as.factor(married))) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Frequency by Marriage/Duration", x = "Duration", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
grid.arrange(want, like, freq)
Try Always
sex_data_try <- sex_data %>%
filter(satis24 == "Always")
want <- ggplot(data = sex_data_try, aes(x = Years_PrimaryPartner, y = want, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Want by Marriage/Duration", x = "Duration", y = "Want", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
like <- ggplot(data = sex_data_try, aes(x = Years_PrimaryPartner, y = totlike, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Like by Marriage/Duration", x = "Duration", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
freq <- ggplot(data = sex_data_try, aes(x = Years_PrimaryPartner, y = freq_num, color = as.factor(married))) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Frequency by Marriage/Duration", x = "Duration", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
grid.arrange(want, like, freq)
Try Often
sex_data_try <- sex_data %>%
filter(satis24 == "Often or most of the time")
want <- ggplot(data = sex_data_try, aes(x = Years_PrimaryPartner, y = want, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Want by Marriage/Duration", x = "Duration", y = "Want", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
like <- ggplot(data = sex_data_try, aes(x = Years_PrimaryPartner, y = totlike, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Like by Marriage/Duration", x = "Duration", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
freq <- ggplot(data = sex_data_try, aes(x = Years_PrimaryPartner, y = freq_num, color = as.factor(married))) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Frequency by Marriage/Duration", x = "Duration", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
grid.arrange(want, like, freq)
Try Sometimes
sex_data_try <- sex_data %>%
filter(satis24 == "Moderate amount of the time")
want <- ggplot(data = sex_data_try, aes(x = Years_PrimaryPartner, y = want, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Want by Marriage/Duration", x = "Duration", y = "Want", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
like <- ggplot(data = sex_data_try, aes(x = Years_PrimaryPartner, y = totlike, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Like by Marriage/Duration", x = "Duration", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
freq <- ggplot(data = sex_data_try, aes(x = Years_PrimaryPartner, y = freq_num, color = as.factor(married))) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Frequency by Marriage/Duration", x = "Age", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
grid.arrange(want, like, freq)
Try Occasionally
sex_data_try <- sex_data %>%
filter(satis24 == "Occasionally or some of the time")
want <- ggplot(data = sex_data_try, aes(x = Years_PrimaryPartner, y = want, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Want by Marriage/Duration", x = "Duration", y = "Want", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
like <- ggplot(data = sex_data_try, aes(x = Years_PrimaryPartner, y = totlike, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Like by Marriage/Duration", x = "Duration", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
freq <- ggplot(data = sex_data_try, aes(x = Years_PrimaryPartner, y = freq_num, color = as.factor(married))) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Frequency by Marriage/Duration", x = "Duration", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
grid.arrange(want, like, freq)
Try Never
sex_data_try <- sex_data %>%
filter(satis24 == "Never")
want <- ggplot(data = sex_data_try, aes(x = Years_PrimaryPartner, y = want, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Want by Marriage/Duration", x = "Duration", y = "Want", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
like <- ggplot(data = sex_data_try, aes(x = Years_PrimaryPartner, y = totlike, color = as.factor(married))) +
geom_point(alpha = .1) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Like by Marriage/Duration", x = "Duration", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
freq <- ggplot(data = sex_data_try, aes(x = Years_PrimaryPartner, y = freq_num, color = as.factor(married))) +
geom_smooth(method = 'lm', se = F) +
jrothsch_theme +
labs(title = "Frequency by Marriage/Duration", x = "Duration", y = "Like", color = "") +
scale_color_discrete(labels = c("Unmarried", "Married"))
grid.arrange(want, like, freq)
Regressions – Marriage
sex_data %>%
lm(want ~ married + age + Years_PrimaryPartner+ MALE + satis24, data = .) %>%
summary()##
## Call:
## lm(formula = want ~ married + age + Years_PrimaryPartner + MALE +
## satis24, data = .)
##
## Residuals:
## Min 1Q Median 3Q Max
## -24.6527 -4.8991 -0.0493 4.8221 27.1469
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 22.295203 0.496783 44.879
## married -0.303632 0.281403 -1.079
## age -0.081556 0.009418 -8.660
## Years_PrimaryPartner -0.079820 0.011555 -6.908
## MALEMale 4.279200 0.227962 18.772
## satis24Occasionally or some of the time 4.563104 0.344129 13.260
## satis24Moderate amount of the time 6.720767 0.358328 18.756
## satis24Often or most of the time 9.401797 0.377770 24.888
## satis24Always 12.547588 0.416989 30.091
## Pr(>|t|)
## (Intercept) < 2e-16 ***
## married 0.281
## age < 2e-16 ***
## Years_PrimaryPartner 5.65e-12 ***
## MALEMale < 2e-16 ***
## satis24Occasionally or some of the time < 2e-16 ***
## satis24Moderate amount of the time < 2e-16 ***
## satis24Often or most of the time < 2e-16 ***
## satis24Always < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.157 on 4189 degrees of freedom
## Multiple R-squared: 0.3593, Adjusted R-squared: 0.358
## F-statistic: 293.6 on 8 and 4189 DF, p-value: < 2.2e-16sex_data %>%
lm(totlike ~ married + age + Years_PrimaryPartner+ MALE + satis24, data = .) %>%
summary()##
## Call:
## lm(formula = totlike ~ married + age + Years_PrimaryPartner +
## MALE + satis24, data = .)
##
## Residuals:
## Min 1Q Median 3Q Max
## -30.6741 -5.2500 0.3337 4.6973 27.0233
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 23.07323 0.51168 45.093
## married -0.08189 0.28984 -0.283
## age 0.02926 0.00970 3.017
## Years_PrimaryPartner -0.05145 0.01190 -4.323
## MALEMale 1.39433 0.23480 5.938
## satis24Occasionally or some of the time 8.31620 0.35445 23.463
## satis24Moderate amount of the time 12.47338 0.36907 33.797
## satis24Often or most of the time 16.54187 0.38910 42.514
## satis24Always 21.54919 0.42949 50.174
## Pr(>|t|)
## (Intercept) < 2e-16 ***
## married 0.77754
## age 0.00257 **
## Years_PrimaryPartner 1.58e-05 ***
## MALEMale 3.11e-09 ***
## satis24Occasionally or some of the time < 2e-16 ***
## satis24Moderate amount of the time < 2e-16 ***
## satis24Often or most of the time < 2e-16 ***
## satis24Always < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.371 on 4189 degrees of freedom
## Multiple R-squared: 0.4614, Adjusted R-squared: 0.4604
## F-statistic: 448.6 on 8 and 4189 DF, p-value: < 2.2e-16sex_data %>%
lm(freq_num ~ married + age + Years_PrimaryPartner+ MALE + satis24, data = .) %>%
summary()##
## Call:
## lm(formula = freq_num ~ married + age + Years_PrimaryPartner +
## MALE + satis24, data = .)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.5189 -0.6600 0.1662 0.8565 3.3691
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 3.202430 0.085058 37.650
## married 0.063494 0.048181 1.318
## age -0.020216 0.001612 -12.538
## Years_PrimaryPartner -0.010851 0.001978 -5.485
## MALEMale 0.169963 0.039031 4.355
## satis24Occasionally or some of the time 1.079696 0.058921 18.325
## satis24Moderate amount of the time 1.294192 0.061352 21.095
## satis24Often or most of the time 1.521265 0.064681 23.520
## satis24Always 1.580606 0.071396 22.139
## Pr(>|t|)
## (Intercept) < 2e-16 ***
## married 0.188
## age < 2e-16 ***
## Years_PrimaryPartner 4.38e-08 ***
## MALEMale 1.37e-05 ***
## satis24Occasionally or some of the time < 2e-16 ***
## satis24Moderate amount of the time < 2e-16 ***
## satis24Often or most of the time < 2e-16 ***
## satis24Always < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.225 on 4189 degrees of freedom
## Multiple R-squared: 0.2913, Adjusted R-squared: 0.29
## F-statistic: 215.2 on 8 and 4189 DF, p-value: < 2.2e-16Regressions – Marriage X Age
sex_data %>%
lm(want ~ married*age + Years_PrimaryPartner+ MALE + satis24, data = .) %>%
summary()##
## Call:
## lm(formula = want ~ married * age + Years_PrimaryPartner + MALE +
## satis24, data = .)
##
## Residuals:
## Min 1Q Median 3Q Max
## -24.641 -4.868 -0.094 4.808 27.027
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 21.51736 0.60261 35.707
## married 1.15259 0.69838 1.650
## age -0.06250 0.01259 -4.964
## Years_PrimaryPartner -0.06971 0.01237 -5.635
## MALEMale 4.30521 0.22813 18.871
## satis24Occasionally or some of the time 4.51568 0.34459 13.105
## satis24Moderate amount of the time 6.69339 0.35835 18.678
## satis24Often or most of the time 9.36772 0.37788 24.790
## satis24Always 12.51743 0.41699 30.018
## married:age -0.03648 0.01602 -2.278
## Pr(>|t|)
## (Intercept) < 2e-16 ***
## married 0.0989 .
## age 7.19e-07 ***
## Years_PrimaryPartner 1.87e-08 ***
## MALEMale < 2e-16 ***
## satis24Occasionally or some of the time < 2e-16 ***
## satis24Moderate amount of the time < 2e-16 ***
## satis24Often or most of the time < 2e-16 ***
## satis24Always < 2e-16 ***
## married:age 0.0228 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.153 on 4188 degrees of freedom
## Multiple R-squared: 0.3601, Adjusted R-squared: 0.3587
## F-statistic: 261.8 on 9 and 4188 DF, p-value: < 2.2e-16sex_data %>%
lm(totlike ~ married * age + Years_PrimaryPartner+ MALE + satis24, data = .) %>%
summary()##
## Call:
## lm(formula = totlike ~ married * age + Years_PrimaryPartner +
## MALE + satis24, data = .)
##
## Residuals:
## Min 1Q Median 3Q Max
## -30.6911 -5.2832 0.3319 4.7047 27.0144
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 22.935661 0.621047 36.931
## married 0.175644 0.719751 0.244
## age 0.032634 0.012977 2.515
## Years_PrimaryPartner -0.049660 0.012750 -3.895
## MALEMale 1.398930 0.235115 5.950
## satis24Occasionally or some of the time 8.307811 0.355130 23.394
## satis24Moderate amount of the time 12.468540 0.369316 33.761
## satis24Often or most of the time 16.535846 0.389440 42.461
## satis24Always 21.543861 0.429751 50.131
## married:age -0.006452 0.016505 -0.391
## Pr(>|t|)
## (Intercept) < 2e-16 ***
## married 0.807
## age 0.012 *
## Years_PrimaryPartner 9.98e-05 ***
## MALEMale 2.90e-09 ***
## satis24Occasionally or some of the time < 2e-16 ***
## satis24Moderate amount of the time < 2e-16 ***
## satis24Often or most of the time < 2e-16 ***
## satis24Always < 2e-16 ***
## married:age 0.696
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.372 on 4188 degrees of freedom
## Multiple R-squared: 0.4614, Adjusted R-squared: 0.4603
## F-statistic: 398.7 on 9 and 4188 DF, p-value: < 2.2e-16sex_data %>%
lm(freq_num ~ married * age + Years_PrimaryPartner+ MALE + satis24, data = .) %>%
summary()##
## Call:
## lm(formula = freq_num ~ married * age + Years_PrimaryPartner +
## MALE + satis24, data = .)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.4610 -0.6672 0.1614 0.8812 3.3421
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 2.856548 0.102809 27.785
## married 0.711030 0.119148 5.968
## age -0.011744 0.002148 -5.467
## Years_PrimaryPartner -0.006357 0.002111 -3.012
## MALEMale 0.181529 0.038921 4.664
## satis24Occasionally or some of the time 1.058609 0.058789 18.007
## satis24Moderate amount of the time 1.282020 0.061137 20.970
## satis24Often or most of the time 1.506113 0.064468 23.362
## satis24Always 1.567197 0.071141 22.029
## married:age -0.016223 0.002732 -5.938
## Pr(>|t|)
## (Intercept) < 2e-16 ***
## married 2.61e-09 ***
## age 4.85e-08 ***
## Years_PrimaryPartner 0.00261 **
## MALEMale 3.20e-06 ***
## satis24Occasionally or some of the time < 2e-16 ***
## satis24Moderate amount of the time < 2e-16 ***
## satis24Often or most of the time < 2e-16 ***
## satis24Always < 2e-16 ***
## married:age 3.13e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.22 on 4188 degrees of freedom
## Multiple R-squared: 0.2972, Adjusted R-squared: 0.2957
## F-statistic: 196.8 on 9 and 4188 DF, p-value: < 2.2e-16