Data · dataset · 2024
Well-matched Marriages Make People Happier? Socioeconomic Status Matching and Marital Satisfaction
Listed in ScienceDB
450 married individuals were recruited through offline recruitment and online response.
Description
We use R language version 4.3.1 for data analysis. Our data consists of 49 items, with the first 14 columns being population statistics tables.
Age "represents the age of the participants," gender "represents their gender," generation "refers to their age," country "refers to their race," region "refers to their place of residence," marriage age "refers to their marriage age, marital status refers to their current marital status, and children refer to the number of children they have. The A and B added after the variable name represent oneself and spouse, respectively.
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Edu "refers to the raw data of the subject's current education level," inc "refers to the raw data of the subject's current income level, and" occ "refers to the raw data of the subject's current occupational level. The variables of 'education', 'income', and 'occupation' are obtained by subtracting the midpoint of the scale from the raw data before conducting response surface analysis. 'Fathereeducation' and 'mothereducation' represent the raw data on the educational level of the parents of the subjects.
Parentedu "refers to the higher score of the two. Parentinc "refers to the raw data of the annual income level of the original family. Parentocc "refers to the raw data of the occupational level of the original family.
Parenteducation, Parentincome, and Parentoccupation refer to the results obtained by subtracting the midpoint of the scale from the original data before conducting response surface analysis. E1~E7 refer to the raw data of the seven items in the Relationship Satisfaction Scale, and "Satis" refers to the total score of marital satisfaction obtained by processing these seven items.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.11550 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Demography 73%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.11550 | 8 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:4403 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (73%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |