Qualtrics Survey Descriptive
Kiet Le
2024-02-12
Purpose:
- This document provides a descriptive statistics and analysis of the survey data collected from Qualtrics. The datasets are cleaned and combined in this script.
Loading R packages
library(tidyverse)
library(here)
library(RColorBrewer)
library(janitor)
library(psych)
library(ggtext)
library(knitr)
library(kableExtra)
library(forcats)
library(gtools)
library(ggrepel)
library(DT)
library(papeR)
library(compareGroups)
library(ggcorrplot)
library(skimr)
library(visdat)
library(VIM)
library(corrplot)Variable Dictionary
dictionary <- data.frame(variable=c("group",
"response",
"awe",
"time_1",
"time_2",
"weekend_1",
"fss_1",
"fss_2",
"fss_3",
"fss_4",
"fss_5",
"fss_6",
"fss_7",
"life_satisfaction_1",
"life_satisfaction_2",
"life_satisfaction_3",
"life_satisfaction_4",
"life_satisfaction_5",
"psych_1",
"psych_2",
"psych_3",
"psych_4",
"psych_5",
"psych_6",
"psych_7",
"psych_8",
"psych_9",
"psych_10",
"psych_11",
"psych_12",
"psych_13",
"psych_14",
"psych_15",
"psych_16",
"psych_17",
"psych_18",
"time_frozen",
"time_connect",
"time_emotion",
"time_immersed",
"time_authenticity",
"sustain_1",
"sustain_2",
"sustain_3",
"sustain_4",
"sustain_5",
"sustain_6",
"sustain_7",
"sustain_8",
"sustain_9",
"sustain_10",
"sustain_11",
"sustain_12",
"sustain_13",
"sustain_14",
"sustain_15",
"time_done",
"time_slipping",
"time_expand",
"time_boundless",
"money_1",
"money_2",
"money_3",
"money_4",
"money_5",
"money_6",
"remember_1",
"remember_2",
"minimalism",
"exper_1",
"exper_2",
"exper_3",
"exper_4",
"exper_5",
"exper_6",
"version",
"responseID",
"prolificID"),
description=c("control, happy, beautiful",
"text response",
"likert-scale response to the statement 'I felt a sense of awe or wonder as I was recalling the experience.'",
"score response to the question 'How quickly did time seem to pass while you were experiencing the recalled experience?'",
"score response to the question 'How long did the remembered experience feel like it lasted?'",
"How far does this weekend feel?",
"I felt strong and in control.",
"I was completely focused on the task at hand.",
"I felt a sense of timelessness.",
"I felt a deep sense of enjoyment.",
"I was absorbed in what I was doing.",
"I felt a sense of personal accomplishment.",
"I lost awareness of external distractions.",
"In most ways my life is close to my ideal.",
"The conditions of my life are excellent.",
"I am satisfied with my life.",
"So far I have gotten the important things I want in life.",
"If I could live my life over, I would change almost nothing.",
"I like most parts of my personality.",
"When I look at the story of my life, I am pleased with how things have turned out so far.",
"Some people wander aimlessly through life, but I am not one of them.",
"The demands of everyday life often get me down.",
"In many ways I feel disappointed about my achievements in life.",
"Maintaining close relationships has been difficult and frustrating for me.",
"I live life one day at a time and don't really think about the future.",
"In general, I feel I am in charge of the situation in which I live.",
"I am good at managing the responsibilities of my daily life.",
"I sometimes feel as if I've done all there is to do in life.",
"For me, life has been a continuous process of learning, changing, and growth.",
"I think it is important to have new experiences that challenge how I think about myself and the world.",
"People would describe me as a giving person, willing to share my time with others.",
"I gave up trying to make big improvements or changes in my life a long time ago.",
"I tend to be influenced by people with strong opinions.",
"I have not experienced many warm and trusting relationships with others.",
"I have confidence in my own opinions, even if they are different from the way most other people think.",
"I judge myself by what I think is important, not by the values of what others think is important.",
"It felt like time was frozen as I was recalling the experience.",
"I was connected to my own self more than ever as I was recalling the experience.",
"I was having a deeper emotional engagement as I was recalling the experience.",
"I was fully present and immersed in the experience as I was recalling it.",
"I felt a sense of authenticity as I was recalling the experience." ,
"Take showers that are 5 minutes or less.",
"Reuse water bottles for as long as possible.",
"Prioritize buying durable clothing that emphasizes quality over quantity.",
"Turn off the lights when you leave your home for an extended period.",
"Conserve energy by turning the heat of air conditioner down when you leave the house.",
"Use electronic methods to pay the bills.",
"Read documents online and avoid print-outs as much as possible.",
"Bring your own bag to the grocery store and minimize all single-use plastics.",
"Reduce your food waste.",
"Buy products with less packaging OR more sustainable packaging.",
"Eat more plants and less meat.",
"Donate to conservation organization.",
"Use a bike to go to work/do errands/etc. (If this is a possibility for you).",
"How long does a 5-minute shower feel like?",
"How would you describe the perceived duration or lifespan of the t-shirt you purchase every six months and subsequently discard? Selecting 'Very short' would indicate that you feel the t-shirt should have been used for a longer period, while selecting 'Very long' would suggest that you feel the t-shirt should have been used for a shorter period.",
"I have lots of time in which I can get things done.",
"Time is slipping away.",
"Time is expanded.",
"Time is boundless.",
"There is more to life than money",
"People who chase money often chase away happiness",
"The best things in life are free",
"To get the most of life, people need money",
"Frankly speaking, having money isn’t all that important to me",
"Frankly speaking, having money is something that I value",
"To what extent did you feel immersed during the time you remembered the experience",
"To what extent did you feel engaged during the time you remembered the experience?",
"If we offered you a one-month free subscription to the Mindful Ownership Assistant (MOA), how likely would you be to use it?",
"Imagine that, as a token of our appreciation for your participation, you could select one of two options below to gift to a loved one. Your loved one could be a significant other, friend, family member, or person you admire. Please choose which option you prefer.",
"If my car or vehicle was in need of simple maintenance or upkeep (e.g., it needed to be cleaned, the wiper blades or light bulbs needed to be replaced, or fluids needed to be checked and replenished), I would...",
"If something in my home was in need of repair or improvement (e.g., walls need to be painted, a shower was clogged, there was a hole in the drywall, or my faucet or toilet was leaky), I would...",
"If I was put in charge of organizing an event (e.g., a party, wedding, or fundraiser), I would...",
"If an item of my clothing was ripped or damaged, I would...",
"If I needed to host a dinner party, I would...",
"Dataset name",
"unique identifier for each participant",
"unique identifier for each participant"))
dictionary %>%
arrange(variable) %>%
kable("html", col.names = c("Variable", "Description")) %>%
kable_styling(bootstrap_options = c("striped", "hover")) %>%
scroll_box(width = "100%", height = "500px")| Variable | Description |
|---|---|
| awe | likert-scale response to the statement ‘I felt a sense of awe or wonder as I was recalling the experience.’ |
| exper_1 | Imagine that, as a token of our appreciation for your participation, you could select one of two options below to gift to a loved one. Your loved one could be a significant other, friend, family member, or person you admire. Please choose which option you prefer. |
| exper_2 | If my car or vehicle was in need of simple maintenance or upkeep (e.g., it needed to be cleaned, the wiper blades or light bulbs needed to be replaced, or fluids needed to be checked and replenished), I would… |
| exper_3 | If something in my home was in need of repair or improvement (e.g., walls need to be painted, a shower was clogged, there was a hole in the drywall, or my faucet or toilet was leaky), I would… |
| exper_4 | If I was put in charge of organizing an event (e.g., a party, wedding, or fundraiser), I would… |
| exper_5 | If an item of my clothing was ripped or damaged, I would… |
| exper_6 | If I needed to host a dinner party, I would… |
| fss_1 | I felt strong and in control. |
| fss_2 | I was completely focused on the task at hand. |
| fss_3 | I felt a sense of timelessness. |
| fss_4 | I felt a deep sense of enjoyment. |
| fss_5 | I was absorbed in what I was doing. |
| fss_6 | I felt a sense of personal accomplishment. |
| fss_7 | I lost awareness of external distractions. |
| group | control, happy, beautiful |
| life_satisfaction_1 | In most ways my life is close to my ideal. |
| life_satisfaction_2 | The conditions of my life are excellent. |
| life_satisfaction_3 | I am satisfied with my life. |
| life_satisfaction_4 | So far I have gotten the important things I want in life. |
| life_satisfaction_5 | If I could live my life over, I would change almost nothing. |
| minimalism | If we offered you a one-month free subscription to the Mindful Ownership Assistant (MOA), how likely would you be to use it? |
| money_1 | There is more to life than money |
| money_2 | People who chase money often chase away happiness |
| money_3 | The best things in life are free |
| money_4 | To get the most of life, people need money |
| money_5 | Frankly speaking, having money isn’t all that important to me |
| money_6 | Frankly speaking, having money is something that I value |
| prolificID | unique identifier for each participant |
| psych_1 | I like most parts of my personality. |
| psych_10 | I sometimes feel as if I’ve done all there is to do in life. |
| psych_11 | For me, life has been a continuous process of learning, changing, and growth. |
| psych_12 | I think it is important to have new experiences that challenge how I think about myself and the world. |
| psych_13 | People would describe me as a giving person, willing to share my time with others. |
| psych_14 | I gave up trying to make big improvements or changes in my life a long time ago. |
| psych_15 | I tend to be influenced by people with strong opinions. |
| psych_16 | I have not experienced many warm and trusting relationships with others. |
| psych_17 | I have confidence in my own opinions, even if they are different from the way most other people think. |
| psych_18 | I judge myself by what I think is important, not by the values of what others think is important. |
| psych_2 | When I look at the story of my life, I am pleased with how things have turned out so far. |
| psych_3 | Some people wander aimlessly through life, but I am not one of them. |
| psych_4 | The demands of everyday life often get me down. |
| psych_5 | In many ways I feel disappointed about my achievements in life. |
| psych_6 | Maintaining close relationships has been difficult and frustrating for me. |
| psych_7 | I live life one day at a time and don’t really think about the future. |
| psych_8 | In general, I feel I am in charge of the situation in which I live. |
| psych_9 | I am good at managing the responsibilities of my daily life. |
| remember_1 | To what extent did you feel immersed during the time you remembered the experience |
| remember_2 | To what extent did you feel engaged during the time you remembered the experience? |
| response | text response |
| responseID | unique identifier for each participant |
| sustain_1 | Take showers that are 5 minutes or less. |
| sustain_10 | Buy products with less packaging OR more sustainable packaging. |
| sustain_11 | Eat more plants and less meat. |
| sustain_12 | Donate to conservation organization. |
| sustain_13 | Use a bike to go to work/do errands/etc. (If this is a possibility for you). |
| sustain_14 | How long does a 5-minute shower feel like? |
| sustain_15 | How would you describe the perceived duration or lifespan of the t-shirt you purchase every six months and subsequently discard? Selecting ‘Very short’ would indicate that you feel the t-shirt should have been used for a longer period, while selecting ‘Very long’ would suggest that you feel the t-shirt should have been used for a shorter period. |
| sustain_2 | Reuse water bottles for as long as possible. |
| sustain_3 | Prioritize buying durable clothing that emphasizes quality over quantity. |
| sustain_4 | Turn off the lights when you leave your home for an extended period. |
| sustain_5 | Conserve energy by turning the heat of air conditioner down when you leave the house. |
| sustain_6 | Use electronic methods to pay the bills. |
| sustain_7 | Read documents online and avoid print-outs as much as possible. |
| sustain_8 | Bring your own bag to the grocery store and minimize all single-use plastics. |
| sustain_9 | Reduce your food waste. |
| time_1 | score response to the question ‘How quickly did time seem to pass while you were experiencing the recalled experience?’ |
| time_2 | score response to the question ‘How long did the remembered experience feel like it lasted?’ |
| time_authenticity | I felt a sense of authenticity as I was recalling the experience. |
| time_boundless | Time is boundless. |
| time_connect | I was connected to my own self more than ever as I was recalling the experience. |
| time_done | I have lots of time in which I can get things done. |
| time_emotion | I was having a deeper emotional engagement as I was recalling the experience. |
| time_expand | Time is expanded. |
| time_frozen | It felt like time was frozen as I was recalling the experience. |
| time_immersed | I was fully present and immersed in the experience as I was recalling it. |
| time_slipping | Time is slipping away. |
| version | Dataset name |
| weekend_1 | How far does this weekend feel? |
Missing values
This table provides the number of missing values for each variable in the dataset
response_id,response,version, andgrouphave no missing values
aggr_plot <- aggr(df, col = c('navajowhite1', 'coral3'), numbers = TRUE, sortVars = TRUE, labels = names(df), cex.axis = 0.7, gap = 3, ylab = c("Histogram of missing data","Pattern"))
##
## Variables sorted by number of missings:
## Variable Count
## money_1 0.93033946
## money_2 0.93033946
## money_3 0.93033946
## money_4 0.93033946
## money_5 0.93033946
## money_6 0.93033946
## time_done 0.92715700
## time_slipping 0.92715700
## time_expand 0.92715700
## time_boundless 0.92715700
## remember_1 0.92715700
## remember_2 0.92715700
## fss_3 0.91478076
## fss_1 0.91442716
## fss_2 0.91442716
## fss_4 0.91442716
## fss_5 0.91442716
## fss_6 0.91442716
## fss_7 0.91442716
## sustain_1 0.89073550
## sustain_2 0.89073550
## sustain_3 0.89073550
## sustain_4 0.89073550
## sustain_5 0.89073550
## sustain_6 0.89073550
## sustain_7 0.89073550
## sustain_8 0.89073550
## sustain_9 0.89073550
## sustain_10 0.89073550
## sustain_11 0.89073550
## sustain_12 0.89073550
## sustain_13 0.89073550
## sustain_14 0.89073550
## sustain_15 0.89073550
## life_satisfaction_1 0.87199434
## life_satisfaction_2 0.87199434
## life_satisfaction_3 0.87199434
## life_satisfaction_4 0.87199434
## life_satisfaction_5 0.87199434
## psych_1 0.87199434
## psych_2 0.87199434
## psych_3 0.87199434
## psych_4 0.87199434
## psych_5 0.87199434
## psych_6 0.87199434
## psych_7 0.87199434
## psych_8 0.87199434
## psych_9 0.87199434
## psych_10 0.87199434
## psych_11 0.87199434
## psych_12 0.87199434
## psych_13 0.87199434
## psych_14 0.87199434
## psych_15 0.87199434
## psych_16 0.87199434
## psych_17 0.87199434
## psych_18 0.87199434
## exper_1 0.67715700
## exper_2 0.67715700
## exper_3 0.67715700
## exper_4 0.67715700
## exper_5 0.67715700
## exper_6 0.67715700
## minimalism 0.63437058
## weekend_1 0.55657709
## time_authenticity 0.54420085
## time_connect 0.47595474
## time_emotional 0.47524752
## time_immersed 0.47524752
## prolific_id 0.33026874
## awe 0.23939180
## time_frozen 0.23727016
## time_1 0.07036775
## time_2 0.07036775
## X 0.00000000
## response_id 0.00000000
## group 0.00000000
## response 0.00000000
## version 0.00000000Summary Statistics
Unique sample size
Checking unique observation and the number of rows is equal to the number of unique
response_idThe current sample size is 2,828
## [1] 2828if (nrow(df) != length(unique(df$response_id))) {
stop("The number of rows does not match the number of unique analytic_id values.")
} else {
# Continue
print("Unique observations check passed.")
}## [1] "Unique observations check passed."Factor variables
df_factor <- df %>% select(group, exper_1, exper_2, exper_3, exper_4, exper_5, exper_6, version)
df_factor %>% mutate_all(as.factor) %>%
summarize_factor() %>%
data.frame() %>%
rename(variable = "X.", Percent = "X..2") %>%
select(-"X..1") %>%
kable(digits = 3,caption = "Summary Statistics",
col.names = c("", "Value", "N", "Percent")) %>%
kable_styling(bootstrap_options = c("striped", "hover")) %>%
collapse_rows(columns = 1, valign = "top") %>%
scroll_box( height = "500px")| Value | N | Percent | |
|---|---|---|---|
| group | beautiful | 1211 | 42.8 |
| control | 348 | 12.3 | |
| happy | 1269 | 44.9 | |
| exper_1 | Receiving a discount coupon for a premade summer berry pie that you can order and have delivered to a loved one | 517 | 18.3 |
| Receiving a recipe for a summer berry pie that you can make and present to a loved one | 396 | 14.0 | |
| <Missing> | 1915 | 67.7 | |
| exper_2 | Do it myself | 558 | 19.7 |
| Have someone else (e.g., a mechanic, car detailer, or car washer) do it for me | 355 | 12.6 | |
| <Missing> | 1915 | 67.7 | |
| exper_3 | Have someone else (e.g., a handyman) try to fix it for me | 313 | 11.1 |
| Try to fix it myself | 600 | 21.2 | |
| <Missing> | 1915 | 67.7 | |
| exper_4 | Create any needed flyers, invitations, announcements, etc. myself | 565 | 20.0 |
| Have someone else create any needed flyers, invitations, announcements, etc. | 348 | 12.3 | |
| <Missing> | 1915 | 67.7 | |
| exper_5 | Have someone else (e.g., a tailor or seamstress) try to repair it for me | 335 | 11.8 |
| Try to repair it myself | 578 | 20.4 | |
| <Missing> | 1915 | 67.7 | |
| exper_6 | Have someone else (e.g., a caterer or chef) prepare and cook the food | 249 | 8.8 |
| Prepare and cook the food myself | 664 | 23.5 | |
| <Missing> | 1915 | 67.7 | |
| version | 07_Beauty_3conditionspilot_withoutphotos | 241 | 8.5 |
| BeautifulMemories_Prolific_Pilot10_Wellbeing | 362 | 12.8 | |
| BeautifulMemories_Prolific_Pilot11_Sustainability | 309 | 10.9 | |
| BeautifulMemories_Prolific_Pilot13_ITC | 265 | 9.4 | |
| BeautifulMemories_Prolific_ShareorNo_onequestion | 199 | 7.0 | |
| Beauty_3conditionspilot_withoutphotos | 159 | 5.6 | |
| Beauty_3conditionspilot_withoutphotos_Experiential_pilot_0 | 242 | 8.6 | |
| Beauty_3conditionspilot_withoutphotos_Pilot4 | 600 | 21.2 | |
| Beauty_3conditionspilot_withoutphotos_SIM_prompt_but_money | 197 | 7.0 | |
| Beauty_3conditionspilot_withoutphotos_SIM_Replicate | 207 | 7.3 | |
| Beauty_3conditionspilot_withoutphotos_SONA | 47 | 1.7 |
Continous variables
df <- df %>%
mutate_at(.vars = vars(awe, fss_1, fss_2, fss_3, fss_4, fss_5, fss_6, fss_7, time_frozen, time_connect, time_emotional, time_immersed, time_authenticity, time_done, time_slipping, time_expand, time_boundless, money_1, money_2, money_3, money_4, money_5, money_6),
.funs=funs(case_when(.=="Strongly Disagree" ~ 1 ,
.=="Moderately Disagree" ~ 2,
.=="Somewhat Disagree" ~3,
.=="Neither Agree nor Disagree" ~ 4,
.=="Somewhat Agree" ~ 5,
.=="Moderately Agree" ~ 6,
.=="Strongly Agree" ~ 7,
TRUE ~ as.numeric(.)))) %>%
mutate_at(.vars = vars(life_satisfaction_1, life_satisfaction_2, life_satisfaction_3, life_satisfaction_4, life_satisfaction_5),
.funs=funs(case_when(.=="Strongly Disagree" ~1,
.=="Disagree" ~ 2,
.=="Slightly Disagree" ~ 3,
.=="Neither Agree nor Disagree" ~ 4,
.=="Slightly Agree" ~ 5,
.=="Agree" ~ 6,
.=="Strongly Agree" ~ 7,
TRUE ~ as.numeric(.)))) %>%
mutate_at(.vars=vars(psych_1, psych_2, psych_3, psych_4, psych_5, psych_6, psych_7, psych_8, psych_9, psych_10, psych_11, psych_12, psych_13, psych_14, psych_15, psych_16, psych_17, psych_18),
.funs=funs(case_when (.=="Strongly Disagree" ~ 1,
.=="Somewhat Disagree" ~ 2,
.=="A Little Disagree" ~ 3,
.=="Neither Agree nor Disagree" ~ 4,
.=="A Little Agree" ~ 5,
.=="Somewhat Agree" ~ 6,
.=="Strongly Agree" ~ 7,
TRUE ~ as.numeric(.))))Overall Summary Statistics
df_cont <- df %>% select(group, time_1, time_2, weekend_1, sustain_1, sustain_2, sustain_3, sustain_4, sustain_5, sustain_6, sustain_7, sustain_8, sustain_9, sustain_10, sustain_11, sustain_12, sustain_13, sustain_14, sustain_15, remember_1, remember_2, minimalism, awe, fss_1, fss_2, fss_3, fss_4, fss_5, fss_6, fss_7, time_frozen, time_connect, time_emotional, time_immersed, time_authenticity, time_done, time_slipping, time_expand, time_boundless, money_1, money_2, money_3, money_4, money_5, money_6, life_satisfaction_1, life_satisfaction_2, life_satisfaction_3, life_satisfaction_4, life_satisfaction_5, psych_1, psych_2, psych_3, psych_4, psych_5, psych_6, psych_7, psych_8, psych_9, psych_10, psych_11, psych_12, psych_13, psych_14, psych_15, psych_16, psych_17, psych_18)
df_cont %>%
select(-group) %>%
describe() %>%
select(n, mean, sd, se, min, max) %>%
clean_names(case = "title") %>%
rename(SD = Sd, SE = Se) %>%
kable(digits = 3, caption = "Summary Statistics of Continous Variable",
col.names = c("", "N", "Mean", "SD", "SE", "Min", "Max")) %>%
kable_styling(bootstrap_options = c("striped", "hover"))%>%
scroll_box( height = "500px")| N | Mean | SD | SE | Min | Max | |
|---|---|---|---|---|---|---|
| time_1 | 2629 | 56.466 | 29.264 | 0.571 | 0 | 100 |
| time_2 | 2629 | 54.867 | 26.563 | 0.518 | 0 | 100 |
| weekend_1 | 1254 | 5.379 | 1.610 | 0.045 | 1 | 7 |
| sustain_1 | 309 | 3.055 | 1.728 | 0.098 | 1 | 6 |
| sustain_2 | 309 | 4.466 | 1.627 | 0.093 | 1 | 6 |
| sustain_3 | 309 | 4.401 | 1.440 | 0.082 | 1 | 6 |
| sustain_4 | 309 | 5.718 | 0.726 | 0.041 | 1 | 6 |
| sustain_5 | 309 | 4.951 | 1.449 | 0.082 | 1 | 6 |
| sustain_6 | 309 | 5.573 | 0.882 | 0.050 | 1 | 6 |
| sustain_7 | 309 | 5.369 | 1.000 | 0.057 | 1 | 6 |
| sustain_8 | 309 | 4.055 | 1.769 | 0.101 | 1 | 6 |
| sustain_9 | 309 | 4.848 | 1.170 | 0.067 | 1 | 6 |
| sustain_10 | 309 | 3.990 | 1.362 | 0.077 | 1 | 6 |
| sustain_11 | 309 | 3.799 | 1.635 | 0.093 | 1 | 6 |
| sustain_12 | 309 | 2.534 | 1.438 | 0.082 | 1 | 6 |
| sustain_13 | 309 | 2.201 | 1.631 | 0.093 | 1 | 6 |
| sustain_14 | 309 | 23.657 | 23.468 | 1.335 | 0 | 100 |
| sustain_15 | 309 | 24.634 | 27.746 | 1.578 | 0 | 100 |
| remember_1 | 206 | 77.481 | 18.739 | 1.306 | 0 | 100 |
| remember_2 | 206 | 78.908 | 18.342 | 1.278 | 0 | 100 |
| minimalism | 1034 | 39.986 | 33.476 | 1.041 | 0 | 100 |
| awe | 1937 | 5.201 | 1.599 | 0.036 | 1 | 7 |
| fss_1 | 192 | 5.562 | 1.471 | 0.106 | 1 | 7 |
| fss_2 | 229 | 6.288 | 1.049 | 0.069 | 1 | 7 |
| fss_3 | 201 | 4.861 | 1.575 | 0.111 | 1 | 7 |
| fss_4 | 218 | 5.560 | 1.673 | 0.113 | 1 | 7 |
| fss_5 | 228 | 6.039 | 1.116 | 0.074 | 1 | 7 |
| fss_6 | 208 | 5.077 | 1.768 | 0.123 | 1 | 7 |
| fss_7 | 217 | 5.198 | 1.639 | 0.111 | 1 | 7 |
| time_frozen | 1873 | 4.304 | 1.810 | 0.042 | 1 | 7 |
| time_connect | 1230 | 5.002 | 1.631 | 0.047 | 1 | 7 |
| time_emotional | 1334 | 5.359 | 1.438 | 0.039 | 1 | 7 |
| time_immersed | 1412 | 5.880 | 1.198 | 0.032 | 1 | 7 |
| time_authenticity | 1213 | 5.163 | 1.876 | 0.054 | 1 | 7 |
| time_done | 62 | 4.968 | 1.765 | 0.224 | 2 | 6 |
| time_slipping | 61 | 5.410 | 1.430 | 0.183 | 2 | 6 |
| time_expand | 37 | 2.649 | 1.495 | 0.246 | 2 | 6 |
| time_boundless | 52 | 2.692 | 1.528 | 0.212 | 2 | 6 |
| money_1 | 181 | 6.033 | 1.187 | 0.088 | 1 | 7 |
| money_2 | 159 | 4.597 | 1.611 | 0.128 | 1 | 7 |
| money_3 | 157 | 4.554 | 1.806 | 0.144 | 1 | 7 |
| money_4 | 183 | 5.601 | 1.292 | 0.096 | 1 | 7 |
| money_5 | 176 | 2.920 | 1.651 | 0.124 | 1 | 7 |
| money_6 | 178 | 5.708 | 1.260 | 0.094 | 1 | 7 |
| life_satisfaction_1 | 340 | 3.982 | 1.964 | 0.107 | 1 | 7 |
| life_satisfaction_2 | 331 | 4.375 | 1.887 | 0.104 | 1 | 7 |
| life_satisfaction_3 | 336 | 4.414 | 1.914 | 0.104 | 1 | 7 |
| life_satisfaction_4 | 331 | 4.523 | 1.895 | 0.104 | 1 | 7 |
| life_satisfaction_5 | 346 | 3.329 | 2.101 | 0.113 | 1 | 7 |
| psych_1 | 348 | 5.733 | 1.369 | 0.073 | 1 | 7 |
| psych_2 | 342 | 4.649 | 2.000 | 0.108 | 1 | 7 |
| psych_3 | 318 | 4.553 | 1.969 | 0.110 | 1 | 7 |
| psych_4 | 333 | 4.093 | 1.925 | 0.105 | 1 | 7 |
| psych_5 | 340 | 3.829 | 2.104 | 0.114 | 1 | 7 |
| psych_6 | 330 | 3.739 | 2.089 | 0.115 | 1 | 7 |
| psych_7 | 329 | 3.079 | 1.841 | 0.102 | 1 | 7 |
| psych_8 | 330 | 4.927 | 1.761 | 0.097 | 1 | 7 |
| psych_9 | 332 | 5.521 | 1.528 | 0.084 | 1 | 7 |
| psych_10 | 340 | 2.206 | 1.603 | 0.087 | 1 | 7 |
| psych_11 | 345 | 6.162 | 1.111 | 0.060 | 1 | 7 |
| psych_12 | 336 | 6.137 | 1.098 | 0.060 | 1 | 7 |
| psych_13 | 334 | 5.611 | 1.458 | 0.080 | 1 | 7 |
| psych_14 | 340 | 2.641 | 1.871 | 0.101 | 1 | 7 |
| psych_15 | 297 | 3.138 | 1.832 | 0.106 | 1 | 7 |
| psych_16 | 342 | 3.146 | 2.063 | 0.112 | 1 | 7 |
| psych_17 | 340 | 5.912 | 1.187 | 0.064 | 1 | 7 |
| psych_18 | 326 | 5.997 | 1.188 | 0.066 | 1 | 7 |
Correlation Matrix
df_matrix <-df_cont %>% select(-group) %>% mutate(across(everything(), as.numeric))
correlation_matrix <- cor(df_matrix, use = "pairwise.complete.obs")
col <- colorRampPalette(c("#BB4444", "#EE9988", "#FFFFFF", "#77AADD", "#4477AA"))
colors <- col(200)
annotation_colors <- c("white", "black")
# Create a correlation heatmap with improved settings
corrplot(correlation_matrix,
method = "color",
col = colors,
type = "upper",
addCoef.col = "black",
tl.col = "black",
tl.srt = 90,
diag = FALSE,
bg = "white",
addrect = 2,
rect.col = "gray",
cl.pos = "n",
number.cex = 0.4, # Adjust the font size for correlation values
tl.cex = 0.5, # Adjust the font size for variable names
addCoef.asPercent = TRUE,
p.mat = NULL,
sig.level = 0.01,
insig = "blank",
pch.col = "black",
pch.cex = 0.8,
col.cor = "black",
mar = c(0,0,1,0))Summary Statistics by Arms
df_happy <- df_cont %>%
filter(group=="happy") %>%
select(-group) %>%
describe() %>%
select(n, mean, sd, se, min, max) %>%
clean_names(case = "title") %>%
rename(SD = Sd, SE = Se) %>%
data.frame()
df_beautiful <- df_cont %>%
filter(group=="beautiful") %>%
select(-group) %>%
describe() %>%
select(n, mean, sd, se, min, max) %>%
clean_names(case = "title") %>%
rename(SD = Sd, SE = Se) %>%
data.frame()
df_control <- df_cont %>%
filter(group=="control") %>%
select(-group) %>%
describe() %>%
select(n, mean, sd, se, min, max) %>%
clean_names(case = "title") %>%
rename(SD = Sd, SE = Se) %>%
data.frame()
df_summary <- cbind(df_happy, df_beautiful, df_control)
df_summary %>%
kable(digits = 3, caption = "Summary Statistics of Continous Variable",
col.names = c("", "N", "Mean", "SD", "SE", "Min", "Max", "N", "Mean", "SD", "SE", "Min", "Max", "N", "Mean", "SD", "SE", "Min", "Max")) %>%
kable_styling(bootstrap_options = c("striped", "hover"))%>%
add_header_above(c(" " = 1, "Happy" = 6, "Beautiful" = 6 , "Control" = 6)) %>%
scroll_box(height = "700px")| N | Mean | SD | SE | Min | Max | N | Mean | SD | SE | Min | Max | N | Mean | SD | SE | Min | Max | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| time_1 | 1164 | 59.422 | 28.907 | 0.847 | 0 | 100 | 1117 | 52.533 | 29.268 | 0.876 | 0 | 100 | 348 | 59.201 | 29.043 | 1.557 | 0 | 100 |
| time_2 | 1164 | 54.578 | 26.793 | 0.785 | 0 | 100 | 1117 | 54.965 | 25.855 | 0.774 | 0 | 100 | 348 | 55.517 | 28.054 | 1.504 | 0 | 100 |
| weekend_1 | 499 | 5.439 | 1.631 | 0.073 | 1 | 7 | 489 | 5.268 | 1.658 | 0.075 | 1 | 7 | 266 | 5.470 | 1.470 | 0.090 | 1 | 7 |
| sustain_1 | 163 | 3.135 | 1.716 | 0.134 | 1 | 6 | 146 | 2.966 | 1.744 | 0.144 | 1 | 6 | 0 | NaN | NA | NA | Inf | -Inf |
| sustain_2 | 163 | 4.491 | 1.557 | 0.122 | 1 | 6 | 146 | 4.438 | 1.706 | 0.141 | 1 | 6 | 0 | NaN | NA | NA | Inf | -Inf |
| sustain_3 | 163 | 4.350 | 1.425 | 0.112 | 1 | 6 | 146 | 4.459 | 1.458 | 0.121 | 1 | 6 | 0 | NaN | NA | NA | Inf | -Inf |
| sustain_4 | 163 | 5.712 | 0.726 | 0.057 | 1 | 6 | 146 | 5.726 | 0.729 | 0.060 | 1 | 6 | 0 | NaN | NA | NA | Inf | -Inf |
| sustain_5 | 163 | 4.939 | 1.386 | 0.109 | 1 | 6 | 146 | 4.966 | 1.520 | 0.126 | 1 | 6 | 0 | NaN | NA | NA | Inf | -Inf |
| sustain_6 | 163 | 5.620 | 0.771 | 0.060 | 1 | 6 | 146 | 5.521 | 0.991 | 0.082 | 1 | 6 | 0 | NaN | NA | NA | Inf | -Inf |
| sustain_7 | 163 | 5.405 | 1.016 | 0.080 | 1 | 6 | 146 | 5.329 | 0.983 | 0.081 | 1 | 6 | 0 | NaN | NA | NA | Inf | -Inf |
| sustain_8 | 163 | 3.969 | 1.814 | 0.142 | 1 | 6 | 146 | 4.151 | 1.719 | 0.142 | 1 | 6 | 0 | NaN | NA | NA | Inf | -Inf |
| sustain_9 | 163 | 4.840 | 1.165 | 0.091 | 1 | 6 | 146 | 4.856 | 1.180 | 0.098 | 1 | 6 | 0 | NaN | NA | NA | Inf | -Inf |
| sustain_10 | 163 | 3.939 | 1.355 | 0.106 | 1 | 6 | 146 | 4.048 | 1.371 | 0.113 | 1 | 6 | 0 | NaN | NA | NA | Inf | -Inf |
| sustain_11 | 163 | 3.761 | 1.559 | 0.122 | 1 | 6 | 146 | 3.842 | 1.721 | 0.142 | 1 | 6 | 0 | NaN | NA | NA | Inf | -Inf |
| sustain_12 | 163 | 2.552 | 1.462 | 0.115 | 1 | 6 | 146 | 2.514 | 1.415 | 0.117 | 1 | 6 | 0 | NaN | NA | NA | Inf | -Inf |
| sustain_13 | 163 | 2.086 | 1.638 | 0.128 | 1 | 6 | 146 | 2.329 | 1.619 | 0.134 | 1 | 6 | 0 | NaN | NA | NA | Inf | -Inf |
| sustain_14 | 163 | 25.104 | 24.550 | 1.923 | 0 | 100 | 146 | 22.041 | 22.170 | 1.835 | 0 | 91 | 0 | NaN | NA | NA | Inf | -Inf |
| sustain_15 | 163 | 24.380 | 27.227 | 2.133 | 0 | 100 | 146 | 24.918 | 28.405 | 2.351 | 0 | 100 | 0 | NaN | NA | NA | Inf | -Inf |
| remember_1 | 68 | 79.456 | 17.977 | 2.180 | 29 | 100 | 68 | 75.544 | 17.480 | 2.120 | 25 | 100 | 70 | 77.443 | 20.621 | 2.465 | 0 | 100 |
| remember_2 | 68 | 82.471 | 16.226 | 1.968 | 32 | 100 | 68 | 75.456 | 17.771 | 2.155 | 27 | 100 | 70 | 78.800 | 20.322 | 2.429 | 0 | 100 |
| minimalism | 424 | 40.124 | 33.804 | 1.642 | 0 | 100 | 417 | 41.347 | 33.995 | 1.665 | 0 | 100 | 193 | 36.744 | 31.512 | 2.268 | 0 | 100 |
| awe | 854 | 5.037 | 1.622 | 0.055 | 1 | 7 | 841 | 5.549 | 1.379 | 0.048 | 1 | 7 | 242 | 4.566 | 1.915 | 0.123 | 1 | 7 |
| fss_1 | 69 | 5.797 | 1.170 | 0.141 | 2 | 7 | 60 | 5.783 | 1.136 | 0.147 | 2 | 7 | 63 | 5.095 | 1.898 | 0.239 | 1 | 7 |
| fss_2 | 81 | 6.407 | 0.891 | 0.099 | 3 | 7 | 72 | 6.278 | 1.141 | 0.134 | 1 | 7 | 76 | 6.171 | 1.112 | 0.128 | 2 | 7 |
| fss_3 | 69 | 4.928 | 1.565 | 0.188 | 1 | 7 | 66 | 5.167 | 1.377 | 0.169 | 1 | 7 | 66 | 4.485 | 1.712 | 0.211 | 1 | 7 |
| fss_4 | 79 | 6.038 | 1.160 | 0.130 | 1 | 7 | 66 | 5.955 | 1.156 | 0.142 | 1 | 7 | 73 | 4.685 | 2.147 | 0.251 | 1 | 7 |
| fss_5 | 81 | 6.111 | 1.049 | 0.117 | 1 | 7 | 71 | 6.141 | 1.175 | 0.139 | 1 | 7 | 76 | 5.868 | 1.124 | 0.129 | 2 | 7 |
| fss_6 | 76 | 5.368 | 1.615 | 0.185 | 1 | 7 | 63 | 5.238 | 1.720 | 0.217 | 1 | 7 | 69 | 4.609 | 1.896 | 0.228 | 1 | 7 |
| fss_7 | 79 | 5.152 | 1.642 | 0.185 | 1 | 7 | 67 | 5.269 | 1.720 | 0.210 | 1 | 7 | 71 | 5.183 | 1.579 | 0.187 | 1 | 7 |
| time_frozen | 841 | 4.197 | 1.825 | 0.063 | 1 | 7 | 792 | 4.354 | 1.823 | 0.065 | 1 | 7 | 240 | 4.517 | 1.692 | 0.109 | 1 | 7 |
| time_connect | 517 | 4.998 | 1.637 | 0.072 | 1 | 7 | 493 | 5.069 | 1.637 | 0.074 | 1 | 7 | 220 | 4.859 | 1.603 | 0.108 | 1 | 7 |
| time_emotional | 556 | 5.396 | 1.379 | 0.058 | 1 | 7 | 535 | 5.383 | 1.439 | 0.062 | 1 | 7 | 243 | 5.222 | 1.559 | 0.100 | 1 | 7 |
| time_immersed | 587 | 5.772 | 1.295 | 0.053 | 1 | 7 | 559 | 5.893 | 1.196 | 0.051 | 1 | 7 | 266 | 6.090 | 0.919 | 0.056 | 2 | 7 |
| time_authenticity | 487 | 5.238 | 1.815 | 0.082 | 1 | 7 | 464 | 5.293 | 1.806 | 0.084 | 1 | 7 | 262 | 4.794 | 2.059 | 0.127 | 1 | 7 |
| time_done | 18 | 4.889 | 1.844 | 0.435 | 2 | 6 | 21 | 4.857 | 1.852 | 0.404 | 2 | 6 | 23 | 5.130 | 1.687 | 0.352 | 2 | 6 |
| time_slipping | 18 | 5.111 | 1.711 | 0.403 | 2 | 6 | 21 | 5.619 | 1.203 | 0.263 | 2 | 6 | 22 | 5.455 | 1.405 | 0.300 | 2 | 6 |
| time_expand | 12 | 2.667 | 1.557 | 0.449 | 2 | 6 | 15 | 2.533 | 1.407 | 0.363 | 2 | 6 | 10 | 2.800 | 1.687 | 0.533 | 2 | 6 |
| time_boundless | 18 | 2.222 | 0.943 | 0.222 | 2 | 6 | 17 | 2.941 | 1.749 | 0.424 | 2 | 6 | 17 | 2.941 | 1.749 | 0.424 | 2 | 6 |
| money_1 | 90 | 6.011 | 1.241 | 0.131 | 1 | 7 | 91 | 6.055 | 1.139 | 0.119 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| money_2 | 78 | 4.538 | 1.593 | 0.180 | 1 | 7 | 81 | 4.654 | 1.637 | 0.182 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| money_3 | 85 | 4.494 | 1.868 | 0.203 | 1 | 7 | 72 | 4.625 | 1.740 | 0.205 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| money_4 | 95 | 5.600 | 1.233 | 0.126 | 1 | 7 | 88 | 5.602 | 1.361 | 0.145 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| money_5 | 91 | 2.967 | 1.810 | 0.190 | 1 | 7 | 85 | 2.871 | 1.470 | 0.159 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| money_6 | 90 | 5.733 | 1.331 | 0.140 | 1 | 7 | 88 | 5.682 | 1.189 | 0.127 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| life_satisfaction_1 | 175 | 3.960 | 1.931 | 0.146 | 1 | 7 | 165 | 4.006 | 2.005 | 0.156 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| life_satisfaction_2 | 178 | 4.427 | 1.853 | 0.139 | 1 | 7 | 153 | 4.314 | 1.931 | 0.156 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| life_satisfaction_3 | 174 | 4.431 | 1.866 | 0.141 | 1 | 7 | 162 | 4.395 | 1.970 | 0.155 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| life_satisfaction_4 | 175 | 4.549 | 1.874 | 0.142 | 1 | 7 | 156 | 4.494 | 1.923 | 0.154 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| life_satisfaction_5 | 180 | 3.333 | 2.090 | 0.156 | 1 | 7 | 166 | 3.325 | 2.118 | 0.164 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_1 | 179 | 5.687 | 1.427 | 0.107 | 1 | 7 | 169 | 5.781 | 1.307 | 0.101 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_2 | 177 | 4.621 | 2.002 | 0.151 | 1 | 7 | 165 | 4.679 | 2.003 | 0.156 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_3 | 164 | 4.512 | 2.011 | 0.157 | 1 | 7 | 154 | 4.597 | 1.929 | 0.155 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_4 | 174 | 4.080 | 1.870 | 0.142 | 1 | 7 | 159 | 4.107 | 1.989 | 0.158 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_5 | 176 | 3.818 | 2.062 | 0.155 | 1 | 7 | 164 | 3.841 | 2.153 | 0.168 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_6 | 173 | 3.688 | 2.031 | 0.154 | 1 | 7 | 157 | 3.796 | 2.157 | 0.172 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_7 | 171 | 3.146 | 1.859 | 0.142 | 1 | 7 | 158 | 3.006 | 1.825 | 0.145 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_8 | 176 | 4.966 | 1.703 | 0.128 | 1 | 7 | 154 | 4.883 | 1.829 | 0.147 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_9 | 176 | 5.528 | 1.493 | 0.113 | 1 | 7 | 156 | 5.513 | 1.572 | 0.126 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_10 | 178 | 2.326 | 1.686 | 0.126 | 1 | 7 | 162 | 2.074 | 1.502 | 0.118 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_11 | 179 | 6.134 | 1.144 | 0.085 | 1 | 7 | 166 | 6.193 | 1.078 | 0.084 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_12 | 171 | 6.053 | 1.123 | 0.086 | 1 | 7 | 165 | 6.224 | 1.067 | 0.083 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_13 | 174 | 5.580 | 1.475 | 0.112 | 1 | 7 | 160 | 5.644 | 1.442 | 0.114 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_14 | 179 | 2.732 | 1.895 | 0.142 | 1 | 7 | 161 | 2.540 | 1.844 | 0.145 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_15 | 153 | 3.092 | 1.865 | 0.151 | 1 | 7 | 144 | 3.188 | 1.801 | 0.150 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_16 | 177 | 3.232 | 2.077 | 0.156 | 1 | 7 | 165 | 3.055 | 2.049 | 0.160 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_17 | 176 | 5.943 | 1.189 | 0.090 | 1 | 7 | 164 | 5.878 | 1.187 | 0.093 | 1 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
| psych_18 | 167 | 5.970 | 1.249 | 0.097 | 1 | 7 | 159 | 6.025 | 1.125 | 0.089 | 2 | 7 | 0 | NaN | NA | NA | Inf | -Inf |
Two-sided mean comparison
test_table <- df_summary %>% data.frame() %>%
select(1:3, 7:9, 13:15)
names(test_table) <- c("n_happy", "mean_happy", "sd_happy", "n_beautiful", "mean_beautiful", "sd_beautiful", "n_control", "mean_control", "sd_control")
calculate_df <- function(s1, s2, n1, n2) {
numerator <- (s1^2 / n1 + s2^2 / n2)^2
denominator <- (s1^2 / n1)^2 / (n1 - 1) + (s2^2 / n2)^2 / (n2 - 1)
df <- numerator / denominator
return(df)
}
test_table <- test_table %>%
mutate(df_happy_beautiful = calculate_df(sd_happy, sd_beautiful, n_happy, n_beautiful),
df_happy_control = calculate_df(sd_happy, sd_control, n_happy, n_control),
df_beautiful_control = calculate_df(sd_beautiful, sd_control, n_beautiful, n_control))
calculate_t_statistic <- function(mean1, mean2, s1, s2, n1, n2) {
numerator <- mean1 - mean2
denominator <- sqrt(s1^2/n1 + s2^2/n2)
t_statistic <- numerator / denominator
return(t_statistic)
}
test_table <- test_table %>%
mutate(t_happy_beautiful = calculate_t_statistic(mean_happy, mean_beautiful, sd_happy, sd_beautiful, n_happy, n_beautiful),
t_happy_control = calculate_t_statistic(mean_happy, mean_control, sd_happy, sd_control, n_happy, n_control),
t_beautiful_control = calculate_t_statistic(mean_beautiful, mean_control, sd_beautiful, sd_control, n_beautiful, n_control))
calculate_p_value <- function(t_statistic, df) {
# Calculate the two-tailed p-value
p_value <- 2 * (1 - pt(abs(t_statistic), df))
# Round the p-value to 3 decimal places
p_value_rounded <- round(p_value, 3)
return(p_value_rounded)
}
test_table <- test_table %>%
mutate(p_happy_beautiful = calculate_p_value(t_happy_beautiful, df_happy_beautiful),
p_happy_control = calculate_p_value(t_happy_control, df_happy_control),
p_beautiful_control = calculate_p_value(t_beautiful_control, df_beautiful_control))
test_table %>%
select(mean_happy, sd_happy, n_happy, mean_beautiful, sd_beautiful, n_beautiful, mean_control, sd_control, n_control, df_happy_beautiful, t_happy_beautiful, p_happy_beautiful, df_happy_control, t_happy_control, p_happy_control, df_beautiful_control, t_beautiful_control, p_beautiful_control) %>%
kable(digits = 3, caption = "T-Test Results",
col.names = c("Mean", "SD", "N", "Mean", "SD", "N", "Mean", "SD", "N", "df", "t-statistics", "p-value", "df", "t-statistics", "p-value", "df", "t-statistics", "p-value")) %>%
kable_styling(bootstrap_options = c("striped", "hover"))%>%
add_header_above(c("Variable" = 1, "Happy" = 3, "Beautiful" = 3 , "Control" = 3, "Happy-Beautiful" = 3, "Happy-Control" = 3, "Beautiful-Control" = 3)) %>%
scroll_box(height = "700px")| Mean | SD | N | Mean | SD | N | Mean | SD | N | df | t-statistics | p-value | df | t-statistics | p-value | df | t-statistics | p-value | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| time_1 | 59.422 | 28.907 | 1164 | 52.533 | 29.268 | 1117 | 59.201 | 29.043 | 348 | 2272.456 | 5.654 | 0.000 | 568.106 | 0.124 | 0.901 | 583.164 | -3.733 | 0.000 |
| time_2 | 54.578 | 26.793 | 1164 | 54.965 | 25.855 | 1117 | 55.517 | 28.054 | 348 | 2278.929 | -0.351 | 0.726 | 549.860 | -0.554 | 0.580 | 543.118 | -0.326 | 0.744 |
| weekend_1 | 5.439 | 1.631 | 499 | 5.268 | 1.658 | 489 | 5.470 | 1.470 | 266 | 984.668 | 1.634 | 0.103 | 591.586 | -0.268 | 0.789 | 602.329 | -1.723 | 0.085 |
| sustain_1 | 3.135 | 1.716 | 163 | 2.966 | 1.744 | 146 | NaN | NA | 0 | 302.165 | 0.858 | 0.392 | NA | NaN | NA | NA | NaN | NA |
| sustain_2 | 4.491 | 1.557 | 163 | 4.438 | 1.706 | 146 | NaN | NA | 0 | 295.076 | 0.281 | 0.779 | NA | NaN | NA | NA | NaN | NA |
| sustain_3 | 4.350 | 1.425 | 163 | 4.459 | 1.458 | 146 | NaN | NA | 0 | 301.644 | -0.664 | 0.507 | NA | NaN | NA | NA | NaN | NA |
| sustain_4 | 5.712 | 0.726 | 163 | 5.726 | 0.729 | 146 | NaN | NA | 0 | 303.048 | -0.173 | 0.863 | NA | NaN | NA | NA | NaN | NA |
| sustain_5 | 4.939 | 1.386 | 163 | 4.966 | 1.520 | 146 | NaN | NA | 0 | 295.029 | -0.163 | 0.871 | NA | NaN | NA | NA | NaN | NA |
| sustain_6 | 5.620 | 0.771 | 163 | 5.521 | 0.991 | 146 | NaN | NA | 0 | 273.094 | 0.973 | 0.332 | NA | NaN | NA | NA | NaN | NA |
| sustain_7 | 5.405 | 1.016 | 163 | 5.329 | 0.983 | 146 | NaN | NA | 0 | 305.154 | 0.669 | 0.504 | NA | NaN | NA | NA | NaN | NA |
| sustain_8 | 3.969 | 1.814 | 163 | 4.151 | 1.719 | 146 | NaN | NA | 0 | 305.998 | -0.902 | 0.368 | NA | NaN | NA | NA | NaN | NA |
| sustain_9 | 4.840 | 1.165 | 163 | 4.856 | 1.180 | 146 | NaN | NA | 0 | 302.383 | -0.117 | 0.907 | NA | NaN | NA | NA | NaN | NA |
| sustain_10 | 3.939 | 1.355 | 163 | 4.048 | 1.371 | 146 | NaN | NA | 0 | 302.456 | -0.703 | 0.482 | NA | NaN | NA | NA | NaN | NA |
| sustain_11 | 3.761 | 1.559 | 163 | 3.842 | 1.721 | 146 | NaN | NA | 0 | 294.221 | -0.436 | 0.663 | NA | NaN | NA | NA | NaN | NA |
| sustain_12 | 2.552 | 1.462 | 163 | 2.514 | 1.415 | 146 | NaN | NA | 0 | 305.139 | 0.235 | 0.815 | NA | NaN | NA | NA | NaN | NA |
| sustain_13 | 2.086 | 1.638 | 163 | 2.329 | 1.619 | 146 | NaN | NA | 0 | 304.024 | -1.309 | 0.192 | NA | NaN | NA | NA | NaN | NA |
| sustain_14 | 25.104 | 24.550 | 163 | 22.041 | 22.170 | 146 | NaN | NA | 0 | 306.978 | 1.153 | 0.250 | NA | NaN | NA | NA | NaN | NA |
| sustain_15 | 24.380 | 27.227 | 163 | 24.918 | 28.405 | 146 | NaN | NA | 0 | 300.005 | -0.169 | 0.866 | NA | NaN | NA | NA | NaN | NA |
| remember_1 | 79.456 | 17.977 | 68 | 75.544 | 17.480 | 68 | 77.443 | 20.621 | 70 | 133.895 | 1.286 | 0.201 | 134.449 | 0.612 | 0.542 | 133.568 | -0.584 | 0.560 |
| remember_2 | 82.471 | 16.226 | 68 | 75.456 | 17.771 | 68 | 78.800 | 20.322 | 70 | 132.906 | 2.404 | 0.018 | 131.121 | 1.174 | 0.242 | 134.533 | -1.030 | 0.305 |
| minimalism | 40.124 | 33.804 | 424 | 41.347 | 33.995 | 417 | 36.744 | 31.512 | 193 | 838.583 | -0.523 | 0.601 | 396.455 | 1.207 | 0.228 | 400.870 | 1.636 | 0.103 |
| awe | 5.037 | 1.622 | 854 | 5.549 | 1.379 | 841 | 4.566 | 1.915 | 242 | 1658.047 | -7.004 | 0.000 | 344.899 | 3.491 | 0.001 | 316.339 | 7.452 | 0.000 |
| fss_1 | 5.797 | 1.170 | 69 | 5.783 | 1.136 | 60 | 5.095 | 1.898 | 63 | 125.443 | 0.068 | 0.946 | 101.375 | 2.528 | 0.013 | 102.223 | 2.452 | 0.016 |
| fss_2 | 6.407 | 0.891 | 81 | 6.278 | 1.141 | 72 | 6.171 | 1.112 | 76 | 133.935 | 0.776 | 0.439 | 143.702 | 1.463 | 0.146 | 145.071 | 0.576 | 0.566 |
| fss_3 | 4.928 | 1.565 | 69 | 5.167 | 1.377 | 66 | 4.485 | 1.712 | 66 | 132.081 | -0.944 | 0.347 | 130.661 | 1.566 | 0.120 | 124.275 | 2.522 | 0.013 |
| fss_4 | 6.038 | 1.160 | 79 | 5.955 | 1.156 | 66 | 4.685 | 2.147 | 73 | 138.598 | 0.432 | 0.666 | 108.767 | 4.780 | 0.000 | 112.751 | 4.397 | 0.000 |
| fss_5 | 6.111 | 1.049 | 81 | 6.141 | 1.175 | 71 | 5.868 | 1.124 | 76 | 141.536 | -0.164 | 0.870 | 152.317 | 1.397 | 0.165 | 143.176 | 1.435 | 0.154 |
| fss_6 | 5.368 | 1.615 | 76 | 5.238 | 1.720 | 63 | 4.609 | 1.896 | 69 | 128.856 | 0.457 | 0.648 | 134.281 | 2.584 | 0.011 | 129.996 | 2.000 | 0.048 |
| fss_7 | 5.152 | 1.642 | 79 | 5.269 | 1.720 | 67 | 5.183 | 1.579 | 71 | 137.795 | -0.417 | 0.677 | 147.299 | -0.119 | 0.906 | 133.274 | 0.304 | 0.762 |
| time_frozen | 4.197 | 1.825 | 841 | 4.354 | 1.823 | 792 | 4.517 | 1.692 | 240 | 1625.388 | -1.729 | 0.084 | 411.320 | -2.533 | 0.012 | 421.079 | -1.285 | 0.200 |
| time_connect | 4.998 | 1.637 | 517 | 5.069 | 1.637 | 493 | 4.859 | 1.603 | 220 | 1005.759 | -0.688 | 0.492 | 421.362 | 1.070 | 0.285 | 428.838 | 1.604 | 0.109 |
| time_emotional | 5.396 | 1.379 | 556 | 5.383 | 1.439 | 535 | 5.222 | 1.559 | 243 | 1081.799 | 0.146 | 0.884 | 414.638 | 1.497 | 0.135 | 436.122 | 1.367 | 0.172 |
| time_immersed | 5.772 | 1.295 | 587 | 5.893 | 1.196 | 559 | 6.090 | 0.919 | 266 | 1142.881 | -1.643 | 0.101 | 700.281 | -4.100 | 0.000 | 660.276 | -2.609 | 0.009 |
| time_authenticity | 5.238 | 1.815 | 487 | 5.293 | 1.806 | 464 | 4.794 | 2.059 | 262 | 947.194 | -0.468 | 0.640 | 479.652 | 2.933 | 0.004 | 485.318 | 3.276 | 0.001 |
| time_done | 4.889 | 1.844 | 18 | 4.857 | 1.852 | 21 | 5.130 | 1.687 | 23 | 36.141 | 0.054 | 0.958 | 34.975 | -0.432 | 0.668 | 40.602 | -0.510 | 0.613 |
| time_slipping | 5.111 | 1.711 | 18 | 5.619 | 1.203 | 21 | 5.455 | 1.405 | 22 | 29.897 | -1.055 | 0.300 | 32.838 | -0.684 | 0.499 | 40.538 | 0.413 | 0.682 |
| time_expand | 2.667 | 1.557 | 12 | 2.533 | 1.407 | 15 | 2.800 | 1.687 | 10 | 22.521 | 0.231 | 0.820 | 18.634 | -0.191 | 0.850 | 16.949 | -0.413 | 0.685 |
| time_boundless | 2.222 | 0.943 | 18 | 2.941 | 1.749 | 17 | 2.941 | 1.749 | 17 | 24.267 | -1.501 | 0.146 | 24.267 | -1.501 | 0.146 | 32.000 | 0.000 | 1.000 |
| money_1 | 6.011 | 1.241 | 90 | 6.055 | 1.139 | 91 | NaN | NA | 0 | 177.349 | -0.248 | 0.805 | NA | NaN | NA | NA | NaN | NA |
| money_2 | 4.538 | 1.593 | 78 | 4.654 | 1.637 | 81 | NaN | NA | 0 | 156.982 | -0.452 | 0.652 | NA | NaN | NA | NA | NaN | NA |
| money_3 | 4.494 | 1.868 | 85 | 4.625 | 1.740 | 72 | NaN | NA | 0 | 153.591 | -0.454 | 0.650 | NA | NaN | NA | NA | NaN | NA |
| money_4 | 5.600 | 1.233 | 95 | 5.602 | 1.361 | 88 | NaN | NA | 0 | 175.613 | -0.012 | 0.991 | NA | NaN | NA | NA | NaN | NA |
| money_5 | 2.967 | 1.810 | 91 | 2.871 | 1.470 | 85 | NaN | NA | 0 | 170.760 | 0.389 | 0.698 | NA | NaN | NA | NA | NaN | NA |
| money_6 | 5.733 | 1.331 | 90 | 5.682 | 1.189 | 88 | NaN | NA | 0 | 174.609 | 0.272 | 0.786 | NA | NaN | NA | NA | NaN | NA |
| life_satisfaction_1 | 3.960 | 1.931 | 175 | 4.006 | 2.005 | 165 | NaN | NA | 0 | 334.888 | -0.216 | 0.829 | NA | NaN | NA | NA | NaN | NA |
| life_satisfaction_2 | 4.427 | 1.853 | 178 | 4.314 | 1.931 | 153 | NaN | NA | 0 | 317.158 | 0.542 | 0.588 | NA | NaN | NA | NA | NaN | NA |
| life_satisfaction_3 | 4.431 | 1.866 | 174 | 4.395 | 1.970 | 162 | NaN | NA | 0 | 328.829 | 0.172 | 0.864 | NA | NaN | NA | NA | NaN | NA |
| life_satisfaction_4 | 4.549 | 1.874 | 175 | 4.494 | 1.923 | 156 | NaN | NA | 0 | 322.614 | 0.263 | 0.793 | NA | NaN | NA | NA | NaN | NA |
| life_satisfaction_5 | 3.333 | 2.090 | 180 | 3.325 | 2.118 | 166 | NaN | NA | 0 | 340.948 | 0.035 | 0.972 | NA | NaN | NA | NA | NaN | NA |
| psych_1 | 5.687 | 1.427 | 179 | 5.781 | 1.307 | 169 | NaN | NA | 0 | 345.682 | -0.641 | 0.522 | NA | NaN | NA | NA | NaN | NA |
| psych_2 | 4.621 | 2.002 | 177 | 4.679 | 2.003 | 165 | NaN | NA | 0 | 338.306 | -0.264 | 0.792 | NA | NaN | NA | NA | NaN | NA |
| psych_3 | 4.512 | 2.011 | 164 | 4.597 | 1.929 | 154 | NaN | NA | 0 | 315.855 | -0.386 | 0.700 | NA | NaN | NA | NA | NaN | NA |
| psych_4 | 4.080 | 1.870 | 174 | 4.107 | 1.989 | 159 | NaN | NA | 0 | 323.525 | -0.125 | 0.901 | NA | NaN | NA | NA | NaN | NA |
| psych_5 | 3.818 | 2.062 | 176 | 3.841 | 2.153 | 164 | NaN | NA | 0 | 333.661 | -0.102 | 0.919 | NA | NaN | NA | NA | NaN | NA |
| psych_6 | 3.688 | 2.031 | 173 | 3.796 | 2.157 | 157 | NaN | NA | 0 | 320.083 | -0.469 | 0.640 | NA | NaN | NA | NA | NaN | NA |
| psych_7 | 3.146 | 1.859 | 171 | 3.006 | 1.825 | 158 | NaN | NA | 0 | 325.784 | 0.688 | 0.492 | NA | NaN | NA | NA | NaN | NA |
| psych_8 | 4.966 | 1.703 | 176 | 4.883 | 1.829 | 154 | NaN | NA | 0 | 314.818 | 0.424 | 0.672 | NA | NaN | NA | NA | NaN | NA |
| psych_9 | 5.528 | 1.493 | 176 | 5.513 | 1.572 | 156 | NaN | NA | 0 | 320.460 | 0.092 | 0.926 | NA | NaN | NA | NA | NaN | NA |
| psych_10 | 2.326 | 1.686 | 178 | 2.074 | 1.502 | 162 | NaN | NA | 0 | 337.849 | 1.456 | 0.146 | NA | NaN | NA | NA | NaN | NA |
| psych_11 | 6.134 | 1.144 | 179 | 6.193 | 1.078 | 166 | NaN | NA | 0 | 342.903 | -0.491 | 0.624 | NA | NaN | NA | NA | NaN | NA |
| psych_12 | 6.053 | 1.123 | 171 | 6.224 | 1.067 | 165 | NaN | NA | 0 | 333.918 | -1.436 | 0.152 | NA | NaN | NA | NA | NaN | NA |
| psych_13 | 5.580 | 1.475 | 174 | 5.644 | 1.442 | 160 | NaN | NA | 0 | 330.742 | -0.396 | 0.692 | NA | NaN | NA | NA | NaN | NA |
| psych_14 | 2.732 | 1.895 | 179 | 2.540 | 1.844 | 161 | NaN | NA | 0 | 335.900 | 0.944 | 0.346 | NA | NaN | NA | NA | NaN | NA |
| psych_15 | 3.092 | 1.865 | 153 | 3.188 | 1.801 | 144 | NaN | NA | 0 | 294.801 | -0.451 | 0.652 | NA | NaN | NA | NA | NaN | NA |
| psych_16 | 3.232 | 2.077 | 177 | 3.055 | 2.049 | 165 | NaN | NA | 0 | 338.912 | 0.793 | 0.428 | NA | NaN | NA | NA | NaN | NA |
| psych_17 | 5.943 | 1.189 | 176 | 5.878 | 1.187 | 164 | NaN | NA | 0 | 336.404 | 0.505 | 0.614 | NA | NaN | NA | NA | NaN | NA |
| psych_18 | 5.970 | 1.249 | 167 | 6.025 | 1.125 | 159 | NaN | NA | 0 | 323.018 | -0.419 | 0.676 | NA | NaN | NA | NA | NaN | NA |
Box plot for each variable across arms
create_boxplots_by_group <- function(data, group, variables) {
# Loop through the list of variables
for (variable in variables) {
# Create a boxplot for each variable
boxplot_formula <- as.formula(paste(variable, "~", group))
boxplot(boxplot_formula,
data = data,
main = paste("Boxplot of", variable, "by", group),
xlab = group,
ylab = variable,
col = "lavender",
border = "darkblue")
}
}
create_boxplots_by_group(df_cont, "group", c("remember_1", "remember_2", "minimalism", "time_1", "time_2", "weekend_1", "sustain_1", "sustain_2", "sustain_3", "sustain_4", "sustain_5", "sustain_6", "sustain_7", "sustain_8", "sustain_9", "sustain_10", "sustain_11", "sustain_12", "sustain_13", "sustain_14", "sustain_15", "awe", "fss_1", "fss_2", "fss_3","fss_4", "fss_5", "fss_6", "fss_7", "time_frozen", "time_connect", "time_emotional", "time_immersed", "time_authenticity", "time_done", "time_slipping", "time_expand", "time_boundless", "money_1", "money_2", "money_3", "money_4", "money_5", "money_6", "life_satisfaction_1", "life_satisfaction_2", "life_satisfaction_3", "life_satisfaction_4", "life_satisfaction_5", "psych_1", "psych_2", "psych_3", "psych_4", "psych_5", "psych_6", "psych_7", "psych_8", "psych_9", "psych_10", "psych_11", "psych_12", "psych_13", "psych_14", "psych_15", "psych_16", "psych_17", "psych_18"))
