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Measuring indoor air pollution in India : an application of quantile regression technique / Tanmoyee Banerjee, Poulomi Roy.
- Format:
- Book
- Author/Creator:
- Banerjee, Tanmoyee, author.
- Roy, Poulomi, author.
- Series:
- SAGE Research methods cases.
- SAGE Research methods cases
- Language:
- English
- Subjects (All):
- Indoor air pollution--Research--India--Case studies.
- Indoor air pollution.
- Quantile regression.
- Physical Description:
- 1 online resource : illustrations.
- Place of Publication:
- London : SAGE Publications Ltd, 2023.
- Summary:
- The case study discusses our methodology in detail and throws light on the use of the quantile regression technique. We clearly explain under what circumstances a researcher would use the quantile regression technique rather than relying upon classical linear regression models.We initiated this project to understand the impact of housing conditions on indoor air pollution caused by cooking with biomass fuel (BMF) in rural areas. Samples were chosen using a multi-stage sampling process that involves complete enumeration for creating a sampling frame. We measured the Carbon Monoxide concentration parts per million(CO ppm) from sampled households that voluntarily joined the survey process. Next, we conducted a primary survey of households for which the measurement survey was undertaken to measure level indoor air pollution and a questionnaire based face-to face interviews were undertaken to collect information on their socio-economic and demographic conditions. In addition, focus group discussions were conducted to gauge the awareness level about adverse effect of using biomass fuel on health condition of the subject and to inform them regarding the same.
- Contents:
- Learning Outcomes Project Overview and Context Research Design Research Practicalities Method in Action Practical Lessons Learned Conclusion Discussion Questions Multiple-Choice Quiz Questions References.
- Notes:
- Includes bibliographical references.
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 1-5296-3088-6
- 9781529630886
- OCLC:
- 1369933122
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