1. ABOUT THE DATASET
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Title: 
Data supporting a paper on the use of institutional data for statistical matching methods, using an example of enrolment in an optional transition course


Creator(s): 
Billy Wong, https://orcid.org/0000-0002-7310-6418
Lydia Fletcher, https://orcid.org/0009-0008-4261-2925


Organisation(s):
University of Reading, UK


Rights-holder(s): 
University of Reading, UK


Publication Year:
2024


Description: 
Anonymised institutional data of undergraduate university students between 2017/18 to 2022/23, collected centrally, showing whether they have enrolled or not enrolled in a university-wide optional online course designed to support student transition into university, mapped against nine other variables of binary data.


Cite as: 
Wong, B, & Fletcher, L. (2024). Data supporting a paper on the use of institutional data for statistical matching methods, using an example of enrolment in an optional transition course. University of Reading. Dataset. https://doi.org/10.17864/1947.001336


Related publication:
Wong, B., & Fletcher, L. (under review). Assessing the impact of a university transition online course on student continuation using statistical matching methods. 


2. TERMS OF USE
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Copyright 2024, University of Reading. This dataset is licensed under a Creative Commons Attribution 4.0 International Licence: https://creativecommons.org/licenses/by/4.0/




3. PROJECT AND FUNDING INFORMATION
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Title: Assessing the impact of a university transition online course on student continuation using statistical matching methods.


This dataset was not created in the course of a funded project


4. CONTENTS
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File listing


Transition_course_data.xlsx


Variable listing


Enrol in transition course (yes, no)
Sex (female, male)
UK domicile (yes, no)
Age group (mature, non-mature)
Ethnicity group (BAME*, white)
Disability status (yes disability, no disability)
DSA [Disability student allowance] (yes DSA, no DSA)
Household income [HHI] (over HHI £25K, under HHI £25K)
POLAR** status (POLAR12, POLAR345)
Pass Year 1 [at 1st or 2nd attempt] (yes, no)

*Black, Asian and Minority Ethnic students (BAME) - acronym is used for grouping purposes only. It is acknowledged there are variations and differences within minority ethnic groups.

**Participation of Local Areas (POLAR) - classification groups areas across the UK based on the proportion of young people who participate in higher education, into quintiles, with 1 being the lowest and 5 being the highest.

In total, 10 variables, 24,411 rows, each row per student:


5. METHODS
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Dataset provided by case-study university using internal data as well as HESA data returns for undergraduate students between 2017/18 to 2022/23.


Data analysed using Stata 18, using the following commands to produce the outputs as reported in paper on regression, propensity score matching and doubly robust estimation:


Please note variable names listed below are slightly different to the variable names as listed in the excel, but these cross-references should be easily identifiable.


ttest markerpass, by(markertransitioncourse)


summarize markersex markeruk markermature markerethnicity markerdisability markerdsa markerincome markerpolar if markertransitioncourse == 1


summarize markersex markeruk markermature markerethnicity markerdisability markerdsa markerincome markerpolar if markertransitioncourse == 0


logistic markertransitioncourse markersex markeruk markermature markerethnicity markerdisability markerdsa markerincome markerpolar 


logistic markerpass markersex markeruk markermature markerbame markerdisability markerdsa markerincome markerpolar 


logit markertransitioncourse markersex markeruk markermature markerethnicity markerdisability markerdsa markerincome markerpolar
predict pscore


tebalance summarize


teffects psmatch (markerpass) (markertransitioncourse markersex markeruk markermature markerethnicity markerdisability markerdsa markerincome markerpolar), atet caliper(0.01) gen(match)


regress markerpass markertransitioncourse markersex markeruk markermature markerethnicity markerdisability markerdsa markerincome markerpolar


teffects aipw (markerpass markersex markeruk markermature markerethnicity markerdisability markerdsa markerincome markerpolar) (markertransitioncourse markersex markeruk markermature markerethnicity markerdisability markerdsa markerincome markerpolar)