added 3 cbs projects

data-prep/data/odissei-projects_CBS.csv

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+title,CBS_project_nr,project_lead,orcid,ODISSEI_grant,publication,data,code,programming language
+"Children's strains, parents' pains? How adult children's union dissolution influences older parents' health",,Damiano Uccheddu,https://orcid.org/0000-0002-6215-203X,NA,https://doi.org/10.20377/jfr-774,"CBS microdata, SHARE",https://doi.org/10.5281/zenodo.7443895,Stata
+Let's Stick Together: Peer Effects in Secondary School Choice and Variations by Student Socio-Economic Background,9232,Dieuwke Zwier,https://orcid.org/0000-0002-5898-5557,NA,https://doi.org/10.1093/esr/jcac033,"CBS microdata, NCO",https://osf.io/xt4cq/,Stata
+"Knowing me, knowing you: Socio-economic status and (segregation in) peer and parental networks in primary school",9232,Dieuwke Zwier,https://orcid.org/0000-0002-5898-5557,NA,https://doi.org/10.1016/j.socnet.2023.03.003,"CBS microdata, PRIMS",https://osf.io/fvqtc/,R
+Statistics Netherlands (CBS) Microdata: Merging datasets (generic),,Erwin Gielens,https://orcid.org/0000-0002-8022-6354,NA,NA,CBS microdata,https://osf.io/46yqp/,R
+"The timing of parental unemployment, insurance and children's education",SES\208008SSBONT_SEC1,Gabriele Mari,https://orcid.org/0000-0001-8557-5337,NA,https://doi.org/10.1080/14616696.2023.2188550,CBS microdata,https://osf.io/wnhm7/,Stata
+Multiple environmental exposures along daily mobility paths and depressive symptoms: A smartphone-based tracking study,8217,Hannah Roberts,https://orcid.org/0000-0001-6978-4737,MAD2020,https://doi.org/10.1016/j.envint.2021.106635,CBS microdata,https://osf.io/ygs72/,R
+Gene-environment interaction analysis of school quality and educational inequality,,Kim Stienstra,https://orcid.org/0000-0002-9877-6215,MAG2019,https://doi.org/10.1038/s41539-024-00225-x,CBS microdata,https://osf.io/xsgdt/,Stata; Mplus
+Diversity in the pathway from medical student to specialist in the Netherlands: a retrospective cohort study,8642,Lianne Mulder,https://orcid.org/0000-0002-7899-2762,MAD2022,https://doi.org/10.1016/j.lanepe.2023.100749,CBS microdata,https://doi.org/10.1016/j.lanepe.2023.100749,SPSS
+Inequality of opportunity in selection procedures limits diversity in higher education: An intersectional study of Dutch selective higher education programs,8642,Lianne Mulder,https://orcid.org/0000-0002-7899-2762,MAD2022,https://doi.org/10.1371/journal.pone.0292805,CBS microdata,https://osf.io/uzcrw?view_only=7114b77c9f8b4062ab31f885ce331a65,SPSS
+NEEDS (Dynamic Urban Environmental Exposures on Depression and Suicide),8217,Marco Helbich,https://orcid.org/0000-0003-0392-8915,MAD2020,https://doi.org/10.1016/j.landurbplan.2021.104181,CBS microdata,https://github.com/UtrechtUniversity/streetview-greenery,Python
+Timing of citizenship acquisition and immigrants' children educational outcomes: a family fixed-effects approach,,Marie Labussi�re,https://orcid.org/0000-0003-4115-7883,NA,https://doi.org/10.1093/esr/jcad027,CBS microdata,https://doi.org/10.7910/DVN/P39QGO,Stata
+Citizenship and education trajectories among children of immigrants: A transition-oriented sequence analysis,,Marie Labussi�re,https://orcid.org/0000-0003-4115-7883,NA,https://doi.org/10.1016/j.alcr.2021.100433,CBS microdata,https://doi.org/10.7910/DVN/VMMMCL,Stata
+"The intergenerational impact of naturalisation reforms: the citizenship status of children of immigrants in the Netherlands, 1995-2016",,Marie Labussi�re,https://orcid.org/0000-0003-4115-7883,NA,https://doi.org/10.1080/1369183X.2020.1724533,CBS microdata,https://doi.org/10.7910/DVN/5XYHJD,Stata
+Inequalities in Healthcare use during the COVID-19 pandemic,8951,Mark Verhagen,https://orcid.org/0000-0003-2746-0309,NA,https://doi.org/10.1038/s41467-024-45720-2,CBS microdata,https://github.com/MarkDVerhagen/Dutch_healthcare_inequalities_COVID19,R
+Evaluating the causal relationship between educational attainment and mental health,8590,Perline Demange,https://orcid.org/0000-0002-7061-8354,MAD2022,https://doi.org/10.1101/2023.01.26.23285029,CBS microdata,https://github.com/PerlineDemange/CBS-MR,R
+"Money, Birth, Gender: Explaining Unequal Earnings Trajectories following Parenthood",9120,Weverthon Barbosa Machado,https://orcid.org/0000-0001-9919-4738,MAD2021,https://doi.org/10.15195/v10.a14,CBS microdata,https://osf.io/gmcjv/,R
+Sex and gender differences in primary care help-seeking for common somatic symptoms: a longitudinal study,8656,Aranka van Ballering,https://orcid.org/0000-0002-3491-8990,NA,https://doi.org/10.1080/02813432.2023.2191653,"Lifelines, NPCD",https://osf.io/7semh/,SPSS
+Medication of Postpartum Depression and Maternal Outcomes: Evidence from Geographic Variation in Dutch Prescribing,8666,Esm�e Zwiers,,NA,https://doi.org/10.3368/jhr.1021-11986R1,CBS microdata,https://jhr.uwpress.org/content/early/2023/06/01/jhr.1021-11986R1/tab-supplemental,Stata
+Defining vulnerability subgroups among pregnant women using pre-pregnancy information: a latent class analysis,8552,Joyce Molenaar,https://orcid.org/0000-0002-8025-040X,NA,https://doi.org/10.1093/eurpub/ckac170,CBS microdata; Perined; Vektis,https://github.com/rivm-syso/DIAPER,Stata

data-prep/data/odissei-projects_LISS.csv

@@ -0,0 +1,13 @@
+title,project_lead,orcid,ODISSEI_grant,publication type,publication,data,link_data,code,programming language
+Hours and income dynamics during the Covid-19 pandemic: The case of the Netherlands,Hans-Martin von Gaudecker,https://orcid.org/0000-0001-8519-9781,,Journal article,https://doi.org/10.1016/j.labeco.2021.102055,LISS panel data,https://doi.org/10.17026/dans-zva-nzcq,https://github.com/ChristianZimpelmann/replication-work-hours-covid/tree/main,Python
+Greed:What Is It Good for?,Karlijn Hoyer,https://orcid.org/0000-0003-4029-9847,LISS Grant 2018,Journal article,https://doi.org/10.1177/01461672221140355,LISS panel data,https://doi.org/10.17026/dans-2xb-7f3j,https://researchbox.org/572,R
+Further tests of the scarcity and luxury hypotheses in dispositional greed: Evidence from two large-scale Dutch and American samples,Karlijn Hoyer,https://orcid.org/0000-0003-4029-9847,LISS Grant 2018,Journal article,https://doi.org/10.1007/s12144-021-02467-z,LISS panel data,https://doi.org/10.17026/dans-2xb-7f3j,https://researchbox.org/177,R
+The wage penalty for informal caregivers from a life course perspective,Klara Raiber,https://orcid.org/0000-0002-9326-8246,LISS Grant 2019,Journal article,https://doi.org/10.1016/j.alcr.2022.100490,LISS panel data,https://doi.org/10.17026/dans-xyf-v7vu,https://github.com/social-scientist/Replication-package-Raiber-Visser-and-Verbakel-2022-Advances-in-life-course-research,Stata
+Are the gender gaps in informal caregiving intensity and burden closing due to the COVID-19 pandemic? Evidence from the Netherlands,Klara Raiber,https://orcid.org/0000-0002-9326-8246,LISS Grant 2019,Journal article,https://doi.org/10.1111/gwao.12725,LISS panel data,"https://doi.org/10.17026/dans-xyf-v7vu; 
+https://doi.org/10.17026/dans-z6w-rd24",https://github.com/social-scientist/Are-the-Gender-Gaps-in-Informal-Caregiving-Intensity-and-Burden-Closing-due-to-the-COVID-19-Pandemic,Stata
+Strategies of informal caregivers to adapt paid work,Klara Raiber,https://orcid.org/0000-0002-9326-8246,LISS Grant 2019,Journal article,https://doi.org/10.1080/14616696.2023.2207108,LISS panel data,https://doi.org/10.17026/dans-xyf-v7vu,https://figshare.com/articles/software/Replication_syntax_article_Strategies_of_Informal_Caregivers_to_Adapt_Paid_Work/22101665,Stata
+Testing the informal care model: intrapersonal change in care provision intensity during the first lockdown of the COVID-19 pandemic,Klara Raiber,https://orcid.org/0000-0002-9326-8246,LISS Grant 2019,Journal article,https://doi.org/10.1007/s10433-022-00713-2,LISS panel data,"https://doi.org/10.17026/dans-xyf-v7vu; 
+https://doi.org/10.17026/dans-z6w-rd24",https://github.com/social-scientist/replication-files-Testing-the-informal-care-model-Raiber-Verbakel-and-de-Boer-2022-,Stata
+The prospective associations between financial scarcity and financial avoidance,Leon Paul Hilbert,https://orcid.org/0000-0002-4366-9332,LISS Grant 2019,Journal article,https://doi.org/10.1016/j.joep.2021.102459,LISS panel data,https://doi.org/10.17026/dans-zha-j8yv,https://doi.org/10.17605/OSF.IO/ZMH5N,R
+"Those were the what? Contents of nostalgia, relative deprivation and radical right support",Peter Luca Versteegen,https://orcid.org/0000-0002-8562-5442,,Journal article,https://doi.org/10.1111/1475-6765.12593,LISS panel data,,https://osf.io/jmsu3/,R
+Does informing citizens about the non-meritocratic nature of inequality bolster support for a universal basic income? Evidence from a population-based survey experiment,Thijs Lindner,https://orcid.org/0000-0003-4377-5968,,Journal article,https://doi.org/10.1080/14616696.2023.2272263,LISS panel data,https://doi.org/10.57990/08zj-b857; https://doi.org/10.17026/dans-x6s-z3ma; https://doi.org/10.17026/dans-z2r-n69z; https://doi.org/10.57990/qn3k-as78,https://osf.io/s364g/,Stata; R

data-prep/scripts/codelibrary_lecture.R

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+library(tidyverse)
+
+cbsdf = read.csv("Data/odissei-projects-clean_CBS.csv")
+lissdf = read.csv("Data/odissei-projects-clean_LISS.csv")
+
+
+colnames(cbsdf)
+colnames(lissdf)
+
+
+df = full_join(cbsdf, lissdf)
+head(df)
+
+
+ggplot(df, aes(x=programming.language)) +
+  geom_bar(fill="dodgerblue") +
+  theme_classic() +
+  xlab("Programming language")
+ggsave("images/prog_lang.jpeg")
+
+
+# repo
+df = df |>
+  mutate(registry = str_match(code, "https:\\/\\/\\s*(.*?)\\s*\\.") %>% .[,2])
+df$registry  
+
+df$registry[df$code=='<a href="https://doi.org/10.17605/OSF.IO/ZMH5N">link</a>'] = "osf"
+df$registry[df$code=='<a href="https://doi.org/10.5281/zenodo.7443895">link</a>'] = "zenodo"
+df$registry[df$code=='<a href="https://doi.org/10.1016/j.lanepe.2023.100749">link</a>'] = "other"
+df$registry[df$code=='<a href="https://doi.org/10.7910/DVN/P39QGO">link</a>'] = "dataverse"
+df$registry[df$code=='<a href="https://doi.org/10.7910/DVN/VMMMCL">link</a>'] = "dataverse"
+df$registry[df$code=='<a href="https://doi.org/10.7910/DVN/5XYHJD">link</a>'] = "dataverse"
+
+ggplot(df, aes(x=registry)) +
+  geom_bar(fill="lightblue") +
+  theme_classic() +
+  xlab("Registry")
+ggsave("images/registry.jpeg")

data-prep/scripts/data_cleaning_CBS.R

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+#' ODISSEI code library -- CBS
+#' Created by Angelica Maineri on 26-06-2023
+#' 
+#' To do:: add hyperlinks to data
+#' 
+
+
+# Load packages
+library(tidyverse)
+
+
+# Load data
+df = read.csv("C:/Users/angel/Documents/GitHub/odissei/ODISSEI-code-library/data-prep/data/odissei-projects_CBS.csv", encoding = "UTF-8")
+
+#### Cleaning ------- 
+# add hyperlinks
+df2 = df |>
+  mutate(publication = if_else(!is.na(publication), paste("<a href=\"", publication, "\">", "doi</a>", sep = ""), " ")) |>
+  mutate(project_lead = paste("<a href=\"", orcid, "\">", project_lead, "</a>", sep = "")) |>
+  mutate(title = paste("<a href=\"", code, "\">", title, "</a>", sep = ""))
+
+
+df2 = df2 |> 
+  select(-c("orcid", "code"))
+
+head(df2)
+
+colnames(df2) = c("Title", "CBS project nr.", "Project lead", "ODISSEI grant", "Publication", "Data", "Code Language")
+
+df2 = df2[,c(1,3,7,5,6,2,4)]
+
+df2$`Project lead` = gsub("<e8>", "è", df2$`Project lead`)
+
+## Export ----
+write.csv(df2, "C:/Users/angel/Documents/GitHub/odissei/ODISSEI-code-library/_data/cbs.csv")
+
+
+

data-prep/scripts/data_cleaning_LISS.R

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+#' ODISSEI code library -- LISS
+#' Created by Angelica Maineri on 06-07-2023
+#' #' 
+#' 
+#' 
+
+
+# Load packages
+library(tidyverse)
+library(stringr)
+
+# Load data
+df = read.csv("C:/Users/angel/Documents/GitHub/odissei/ODISSEI-code-library/Data/odissei-projects_LISS.csv", encoding = "UTF-8")
+
+#### Cleaning ------- 
+# add hyperlinks
+df2 = df |>
+  mutate(publication = if_else(!is.na(publication), paste("<a href=\"", publication, "\">", "doi</a>", sep = ""), " ")) |>
+  mutate(project_lead = paste("<a href=\"", orcid, "\">", project_lead, "</a>", sep = "")) |>
+  mutate(title = paste("<a href=\"", code, "\">", title, "</a>", sep = ""))
+
+
+df2$link_data = gsub('https://','<a href="https://', df2$link_data )
+df2$link_data = gsub('*$','">data</a>', df2$link_data )
+df2$link_data = gsub(';','">data</a>;', df2$link_data )
+df2$link_data[df2$link_data=='\">data</a>'] = ""
+
+df2$link_data
+df2$project_lead
+
+
+
+df2 = df2 |> 
+  select(-c("orcid", "publication.type", "code"))
+
+head(df2)
+
+colnames(df2) = c("Title", "Project lead", "ODISSEI grant", "Publication", "Data", "Link to data", "Code Language")
+df2 = df2[,c(1,2,7,4,5,6,3)]
+
+## Export ----
+write.csv(df2, "Data/odissei-projects-clean_LISS.csv")

data-prep/scripts/script.Rmd

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+---
+title: "ODISSEI code library <img src=\"C:/Users/angel/Documents/GitHub/ODISSEI-code-library/images/odissei_logo.png\" style=\"float: right;\" width=\"250\" height=\"70\" />"
+author: 
+  name: "ODISSEI FAIR support team "
+  email: "[email protected]"
+  affiliation: "Erasmus University Rotterdam - ODISSEI"
+date: '`r Sys.Date()`'
+knit: (function(inputFile, encoding) {
+  rmarkdown::render(inputFile, encoding = "UTF-8", output_file="C:/Users/angel/Documents/GitHub/odissei/ODISSEI-code-library/docs/index.html") })
+output: 
+  html_document:
+    theme: cosmo
+    toc: yes
+    toc_float:
+      collapsed: false
+    css: docs.css
+---
+
+```{r setup, include=FALSE}
+knitr::opts_chunk$set(echo = FALSE, message = FALSE)
+suppressWarnings(library(DT))
+suppressWarnings(library(tidyverse))
+suppressWarnings(library(stringr))
+```
+
+
+# Welcome
+The ODISSEI code library contains a collection of scripts detailing data processing and analysis steps of projects using LISS panel data and CBS (Statistics Netherlands) microdata. Some of the projects receive funding via [ODISSEI](https://odissei-data.nl/en/).
+
+If you have comments, reach out to the [ODISSEI FAIR support team](mailto:[email protected]).
+
+Do you want to submit your own project and code to be added to the library? Please submit an issue using the Submission code issue template on the [GitHub repository](https://github.com/odissei-data/ODISSEI-code-library) or send an email to the [ODISSEI FAIR support team](mailto:[email protected]).
+
+# Code libraries
+## CBS microdata 
+```{r loaddataCBS}
+df = read.csv("C:/Users/angel/Documents/GitHub/odissei/ODISSEI-code-library/Data/odissei-projects-clean_CBS.csv", encoding = "UTF-8", check.names=FALSE)
+colnames(df)[1] = c("X")
+df = df |> dplyr:::select(-c("X")) 
+DT::datatable(df, escape = FALSE,
+              filter = "top", 
+              options = list(dom = "ft", 
+                            pageLength = 1000, 
+                            autoWidth = TRUE),
+              rownames = FALSE)
+```
+
+## LISS panel
+```{r loaddataLISS}
+df2 = read.csv("C:/Users/angel/Documents/GitHub/odissei/ODISSEI-code-library/Data/odissei-projects-clean_LISS.csv", encoding = "UTF-8", check.names=FALSE)
+colnames(df2)[1] = c("X")
+df2 = df2 |> dplyr:::select(-c("X")) 
+DT::datatable(df2, escape = FALSE,
+              filter = "top", 
+              options = list(dom = "ft", 
+                            pageLength = 1000, 
+                            autoWidth = TRUE),
+              rownames = FALSE)
+```