Questions and Answers
What is the AOR for motorcyclists with a positive blood alcohol level sustaining fatal injuries?
What percentage more likely were pediatric casualties to sustain KSI on Halloween between 17:00 to 16:00?
What is the RERI value for the interaction effect between drunk and unhelmeted riding?
What is the benefit of secondary data analysis?
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What type of dataset was used in the study?
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What software was used for data analysis in the study?
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What is the AOR for unhelmeted motorcyclists sustaining fatal injuries?
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Why is it important to research the combined effect of risk factors?
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What was done to cases with missing data in the study?
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What is the benefit of using secondary datasets for students?
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Study Notes
Definition and Types of Secondary Data Research
- Secondary data research involves using data collected for other purposes, which can be collected by the same team or provided by other sources such as government, NGOs, universities, literature reviews, or hospitals.
Sources of Secondary Data
- Government sources: Riskesdas, SDKI, BPJS, BPS
- NGO sources: IFLS
- University sources: HDSS
- Literature reviews
- Hospital sources: medical records
Examples of Available Secondary Datasets in Indonesia
- Indonesia Family Life Survey (IFLS): 5 waves since 1993, every 5 years, longitudinal survey
- Indonesia Demographic and Health Survey (IDHS or SDKI): every 5 years since 1997, repeated cross-sectional
- Basic Health Research (Riskesdas): 2007, 2010, 2013, 2018, repeated cross-sectional
- BPJS dataset: 2015-2021, every year, longitudinal for 1% sample from all BPJS participants
Examples of Available Datasets Outside Indonesia
- USA: CDC BRFSS, CDC YRBSS, FARS, etc.
- World Bank: World Bank open data
- UK: STATS-19 UK (accident database from 1979)
Advantages of Secondary Data Research
- Cost savings
- Time efficiency
- Access to large, complex datasets
- Ability to explore new research questions or test hypotheses
Challenges of Secondary Data Research
- Data quality issues cannot be modified
- Limited data availability
- Data compatibility issues due to different sources and formats
- Data bias introduction due to new hypotheses
- Data ethics concerns
- Need for advanced data management skills
- Limited data documentation
Data Preparation
- Combining data from different sources
- Managing missing data: deciding whether data is missing at random, and using imputation if necessary
Data Analysis
- Similar to primary data analysis: using chi-square, t-tests, regression, multilevel/panel data
- Need to use complex data analysis techniques to improve novelty, such as interaction analysis, mediation, and multilevel analysis
Ethical Considerations
- Need ethical clearance
- Usually no informed consent is needed
- Data should be anonymized (no names or identifiers)
Case Study: UK Traffic Dataset
- Analyzed UK STATS19 crash data from 1990-2017
- Found that incidents resulting in child pedestrian fatalities are most frequent during spring and fall
- Found that pediatric casualties on Halloween were 34.2% more likely to sustain KSIs than on other days
Interaction Analysis Using Secondary Database
- Need to research combined effects of multiple risk factors
- Example: interaction effect between drunk and unhelmeted riding on motorcyclist fatalities
- Used National Taiwan crash dataset from 2011-2015, and found a positive interaction effect between drunk and unhelmeted riding
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Description
This quiz covers the definition, types, and sources of secondary data research, including government, NGO, university, literature review, and hospital sources.
