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Case uitwerking (Outputbestand) Onderzoekspracticum longitudinaal onderzoek (PB1712)

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Case Uitwerking Onderzoekspracticum Longitudinaal Onderzoek (PB1712) – Output Omschrijving: Ben je bezig met de cursus Onderzoekspracticum Longitudinaal Onderzoek (PB1712) en wil je excelleren in je werk? Deze uitgebreide bundel bevat alle onderdelen die nodig zijn voor een succesvol longitudinaal onderzoek: Abstract, Output, Syntax en Presentatieslides. Wij hebben een 9.1 behaald voor ons onderzoek, en nu kun jij profiteren van onze zorgvuldige en hoogwaardige aanpak! Deze bundel is ideaal voor studenten die hun longitudinaal onderzoek willen versterken met praktische voorbeelden en inspiratie. Gebruik deze uitwerking als gids en till je werk naar een hoger niveau! Let op: Deze uitwerking is bedoeld als hulpmiddel en ter inspiratie. Gebruik het als aanvulling op je eigen werk en zorg voor een unieke invulling van je onderzoek.

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Uploaded on
January 3, 2025
Number of pages
30
Written in
2024/2025
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Case
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Effect Yoga/Fitness op Burnout


knitr::opts_chunk$set(width.cutoff = 50)
knitr::opts_chunk$set(echo = FALSE)


Load in required libraries
## Welcome to emmeans.
## Caution: You lose important information if you filter this package's results.
## See '? untidy'

##
## Attaching package: 'jmvcore'

## The following objects are masked from 'package:base':
##
## endsWith, format, startsWith

## -- Attaching core tidyverse packages ------------------------ tidyverse 2.0.0 --
## v dplyr 1.1.4 v readr 2.1.5
## v forcats 1.0.0 v stringr 1.5.1
## v ggplot2 3.5.1 v tibble 3.2.1
## v lubridate 1.9.3 v tidyr 1.3.1
## v purrr 1.0.2
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::collapse() masks nlme::collapse()
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
## x dplyr::select() masks jmvcore::select()
## i Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become err


Read in the data
## # A tibble: 6 x 7
## Respnum Vestiging Tijd Burnout Conditie Sekse Leeftijd
## <dbl> <dbl> <dbl> <dbl> <dbl+lbl> <dbl+lbl> <dbl>
## 1 108 29 4 3.59 2 [yoga] 0 [man] 37.0
## 2 34 8 3 2.95 1 [fitness] 0 [man] 30.8
## 3 31 23 2 3.80 1 [fitness] 0 [man] 43.3
## 4 151 5 1 4.62 2 [yoga] 1 [vrouw] 42.8
## 5 2 15 6 2.32 1 [fitness] 0 [man] 45.4
## 6 264 30 4 3.34 3 [controle] 1 [vrouw] 45.4

Tranform data: correct variable types


1

, Descriptive statistics

Check how sound the data is

##
## DESCRIPTIVES
##
## Descriptives
## ������������������������������������������������������������������������������������������������
## N Missing Mean Median SD Minimum Maximum
## ������������������������������������������������������������������������������������������������
## Burnout 2160 0 4.451827 4.296333 1.995177 0.6589023 10.000000
## Tijd 2160 0 3.507870 3.000000 2.293825 0.0000000 7.000000
## Conditie 2160 0
## Sekse 2160 0
## Leeftijd 2160 0 45.732342 46.061806 7.809702 18.2605629 67.153295
## ������������������������������������������������������������������������������������������������
##
##
## FREQUENCIES
##
## Frequencies of Conditie
## ����������������������������������������������������
## Conditie Counts % of Total Cumulative %
## ����������������������������������������������������
## controle 717 33.19444 33.19444
## yoga 719 33.28704 66.48148
## fitness 724 33.51852 100.00000
## ����������������������������������������������������
##
##
## Frequencies of Sekse
## �������������������������������������������������
## Sekse Counts % of Total Cumulative %
## �������������������������������������������������
## vrouw 1075 49.76852 49.76852
## man 1085 50.23148 100.00000
## �������������������������������������������������

Inspection of these descriptive statistics:

• Burnout scores UBOS scale should not be lower than 1: remove lower-than-1 values

Now check how many participants we have in the data and how many participants have data for each
timepoint:
How many timepoints per participant?




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