if (!require(haven)){
install.packages("haven", dependencies = TRUE)
require(haven)}Loading required package: havenSurvey results
Loading Packages
if (!require(tidyverse)){
install.packages("tidyverse", dependencies = TRUE)
require(tidyverse)}Loading required package: tidyverse── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr 1.1.2 ✔ readr 2.1.4
✔ forcats 1.0.0 ✔ stringr 1.5.0
✔ ggplot2 3.4.4 ✔ tibble 3.2.1
✔ lubridate 1.9.2 ✔ tidyr 1.3.0
✔ purrr 1.0.2
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorsif (!require(summarytools)){
install.packages("summarytools", dependencies = TRUE)
require(summarytools)}Loading required package: summarytoolsWarning in fun(libname, pkgname): couldn't connect to display ":0"system might not have X11 capabilities; in case of errors when using dfSummary(), set st_options(use.x11 = FALSE)
Attaching package: 'summarytools'The following object is masked from 'package:tibble':
viewif (!require(psych)){
install.packages("psych", dependencies = TRUE)
require(psych)}Loading required package: psych
Attaching package: 'psych'The following objects are masked from 'package:ggplot2':
%+%, alphaif (!require(afex)){
install.packages("afex", dependencies = TRUE)
require(afex)}Loading required package: afexLoading required package: lme4Loading required package: Matrix
Attaching package: 'Matrix'The following objects are masked from 'package:tidyr':
expand, pack, unpack************
Welcome to afex. For support visit: http://afex.singmann.science/- Functions for ANOVAs: aov_car(), aov_ez(), and aov_4()
- Methods for calculating p-values with mixed(): 'S', 'KR', 'LRT', and 'PB'
- 'afex_aov' and 'mixed' objects can be passed to emmeans() for follow-up tests
- Get and set global package options with: afex_options()
- Set sum-to-zero contrasts globally: set_sum_contrasts()
- For example analyses see: browseVignettes("afex")
************
Attaching package: 'afex'The following object is masked from 'package:lme4':
lmerImport Data
dataset <- read_sav("Survey data(Slayyy Group).sav")Clean Data
(dataset %>%
filter(Duration__in_seconds_ > 100) -> dataset.clean)# A tibble: 58 × 37
StartDate EndDate Status IPAddress Progress
<dttm> <dttm> <dbl+lbl> <chr> <dbl>
1 2024-03-13 15:49:51 2024-03-13 15:53:13 0 [IP Address] 24.73.113.90 100
2 2024-03-13 20:32:30 2024-03-13 20:34:51 0 [IP Address] 68.204.241.26 100
3 2024-03-13 20:52:23 2024-03-13 20:57:15 0 [IP Address] 174.211.235.… 100
4 2024-03-13 20:58:28 2024-03-13 21:02:02 0 [IP Address] 99.59.219.51 100
5 2024-03-13 21:01:32 2024-03-13 21:03:24 0 [IP Address] 104.56.90.38 100
6 2024-03-13 21:03:57 2024-03-13 21:06:17 0 [IP Address] 184.91.87.110 100
7 2024-03-13 21:04:12 2024-03-13 21:07:59 0 [IP Address] 96.58.64.252 100
8 2024-03-13 21:09:34 2024-03-13 21:12:34 0 [IP Address] 47.197.226.1… 100
9 2024-03-13 21:20:56 2024-03-13 21:23:09 0 [IP Address] 73.192.7.69 100
10 2024-03-13 22:23:50 2024-03-13 22:29:50 0 [IP Address] 209.99.207.2… 100
# ℹ 48 more rows
# ℹ 32 more variables: Duration__in_seconds_ <dbl>, Finished <dbl+lbl>,
# RecordedDate <dttm>, ResponseId <chr>, RecipientLastName <chr>,
# RecipientFirstName <chr>, RecipientEmail <chr>, ExternalReference <chr>,
# LocationLatitude <chr>, LocationLongitude <chr>, DistributionChannel <chr>,
# UserLanguage <chr>, Informed_Consent <dbl+lbl>, Easy_1 <dbl+lbl>,
# Easy_2 <dbl+lbl>, Easy_3 <dbl+lbl>, Easy_4 <dbl+lbl>, Easy_5 <dbl+lbl>, …(dataset %>%
filter(Progress > 100) -> dataset.clean)# A tibble: 0 × 37
# ℹ 37 variables: StartDate <dttm>, EndDate <dttm>, Status <dbl+lbl>,
# IPAddress <chr>, Progress <dbl>, Duration__in_seconds_ <dbl>,
# Finished <dbl+lbl>, RecordedDate <dttm>, ResponseId <chr>,
# RecipientLastName <chr>, RecipientFirstName <chr>, RecipientEmail <chr>,
# ExternalReference <chr>, LocationLatitude <chr>, LocationLongitude <chr>,
# DistributionChannel <chr>, UserLanguage <chr>, Informed_Consent <dbl+lbl>,
# Easy_1 <dbl+lbl>, Easy_2 <dbl+lbl>, Easy_3 <dbl+lbl>, Easy_4 <dbl+lbl>, …(dataset %>%
filter(Finished > 1) -> dataset.clean)# A tibble: 0 × 37
# ℹ 37 variables: StartDate <dttm>, EndDate <dttm>, Status <dbl+lbl>,
# IPAddress <chr>, Progress <dbl>, Duration__in_seconds_ <dbl>,
# Finished <dbl+lbl>, RecordedDate <dttm>, ResponseId <chr>,
# RecipientLastName <chr>, RecipientFirstName <chr>, RecipientEmail <chr>,
# ExternalReference <chr>, LocationLatitude <chr>, LocationLongitude <chr>,
# DistributionChannel <chr>, UserLanguage <chr>, Informed_Consent <dbl+lbl>,
# Easy_1 <dbl+lbl>, Easy_2 <dbl+lbl>, Easy_3 <dbl+lbl>, Easy_4 <dbl+lbl>, …(dataset %>%
filter(Age > 18) -> dataset.clean)# A tibble: 60 × 37
StartDate EndDate Status IPAddress Progress
<dttm> <dttm> <dbl+lbl> <chr> <dbl>
1 2024-03-13 15:49:51 2024-03-13 15:53:13 0 [IP Address] 24.73.113.90 100
2 2024-03-13 20:32:30 2024-03-13 20:34:51 0 [IP Address] 68.204.241.26 100
3 2024-03-13 20:52:23 2024-03-13 20:57:15 0 [IP Address] 174.211.235.… 100
4 2024-03-13 20:58:28 2024-03-13 21:02:02 0 [IP Address] 99.59.219.51 100
5 2024-03-13 21:01:32 2024-03-13 21:03:24 0 [IP Address] 104.56.90.38 100
6 2024-03-13 21:03:57 2024-03-13 21:06:17 0 [IP Address] 184.91.87.110 100
7 2024-03-13 21:04:12 2024-03-13 21:07:59 0 [IP Address] 96.58.64.252 100
8 2024-03-13 21:09:34 2024-03-13 21:12:34 0 [IP Address] 47.197.226.1… 100
9 2024-03-13 21:20:56 2024-03-13 21:23:09 0 [IP Address] 73.192.7.69 100
10 2024-03-13 22:23:50 2024-03-13 22:29:50 0 [IP Address] 209.99.207.2… 100
# ℹ 50 more rows
# ℹ 32 more variables: Duration__in_seconds_ <dbl>, Finished <dbl+lbl>,
# RecordedDate <dttm>, ResponseId <chr>, RecipientLastName <chr>,
# RecipientFirstName <chr>, RecipientEmail <chr>, ExternalReference <chr>,
# LocationLatitude <chr>, LocationLongitude <chr>, DistributionChannel <chr>,
# UserLanguage <chr>, Informed_Consent <dbl+lbl>, Easy_1 <dbl+lbl>,
# Easy_2 <dbl+lbl>, Easy_3 <dbl+lbl>, Easy_4 <dbl+lbl>, Easy_5 <dbl+lbl>, …