ArticleSocial science research2019
The utility of a follow-up interview for respondents to a longitudinal survey with frequent measurement.
Article in Social science research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Using Paradata to Evaluate Youth Participation in a Digital Diary Study.Social science computer review · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Social processes that change quickly are difficult to study, because they require frequent survey measurement. Weekly, daily, or even hourly measurement may be needed depending on the topic. With more frequent measurement comes the prospect of more complex patterns of missing data. The mechanisms creating the missing data may be varied, ranging from technical issues such as lack of an Internet connection to refusal to complete a requested survey. We examine one approach to mitigating the damage of these missing data - a follow-up or closeout interview that is completed after the frequent measurement. The Relationship Dynamics and Social Life (RDSL) study used this approach. The study asked women weekly about their attitudes and behaviors related to sexual relationships and pregnancy. The surveys were carried out for 130 weeks and concluded with a closeout interview. We explore the patterns of missing data in the RDSL study and then examine associations between the data collected in the closeout survey and key variables collected in the weekly survey. We then assess the extent to which data from the closeout survey are useful in repairing the damage caused by missing data.
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