Dr. Akansha Singh
Assistant Professor (Research)
I am a progressive intellectual, never shy away from disclosing interesting facts about the data and my research. I am always keen to apply my knowledge of statistics to other related disciplines of science and social science in an innovative way. As an experienced researcher and statistician, I would like to bring a fresh and inspiring voice to the research arena.
Akansha Singh
My research is interdisciplinary, at the crossroads of statistics, demography and public health and area of expertise are Survey Data Analysis and Methods, Biostatistics, Applied Statistics, Mathematical Demography, Mortality and Health, and multilevel analysis.
I have vast experience of handling information from large population or behavioral data sources like Demographic Health Surveys, educational trials or census data, which makes me well versed in different sampling designs, types of data, estimation using SAS, R, Excel, SPSS, STATA, and MLwiN. I can disseminate my research output in the form of papers in various national/international academic forums and leading international journals in the field of population health and statistics. I have experience of working in three international projects Educational Endownment Foundation Educational Trials, UK, Longitudinal Ageing Study in India and Global Adult Tobacco Survey Project and worked with international collaborators Educational Endowment Foundation in the UK and Harvard School of Public Health, WHO and CDC Atlanta in the USA.
Representative Publications
Continuities and changes in spatial patterns of under-five mortality at the district level in India (1991–2011)
November 15, 2018
This study seeks to unravel local variation in key determinants of under-five mortality based on the 1991 and 2011 censuses. Using geocoded district-level data from the last two census rounds (1991 and 2011) and ordinary least squares and geographically weighted regressions, we identify district-specific relationships between under-five mortality rate and a series of determinants for two periods separated by 20 years (1986–1987 and 2006–2007) using R software. To identify spatial groupings of coefficients, we perform a cluster analysis based on t-values of the geographically weighted regression.
Classification of nicotine-dependent users in India: a decision-tree approach
September 05, 2018
The main objective of the present research is to characterize nicotine dependency related to smoking and smokeless tobacco among adults according to age, education level, duration of use and other socioeconomic characteristics.
We analyzed Global Adult Tobacco Survey (GATS) 2010 data for 9190 smokers and 13,357 smokeless tobacco users who were 15 years of age or older. Time to first tobacco use of the day was used as a measure of nicotine dependence. We employed a decision tree algorithm from SAS Enterprise Miner to conduct classification analysis to establish the relationship among nicotine dependency for smoking, smokeless tobacco use, and its predictors.
Measuring early life disparity in India
July, 2016
Early life disparity – defined as the average life years lost due to death by the age of 60 years – can be used to assess more systematically the effect of savings from death at a young age. In addition, it can give valuable insight into the consequences of death in the early stages of life. The findings clearly indicated an overall declining trend in early life disparity in India, with a notable reduction in child life disparity, and a deceleration of adult life disparity during the period 1970–1975 to 2006–2010. Interstate variations in early life disparity were seen to converge with time. Decomposition analysis suggested that these variations could be minimized further by averting death during childhood.
Prevalence and Determinants of Tobacco Use in India: Evidence from Recent Global Adult Tobacco Survey Data
December, 2014
We analyzed a cross-sectional, nationally representative sample of individuals from the Global Adult Tobacco Survey in India (2009–10), which covered 69,296 individuals aged 15 years and above. The current tobacco use in three forms, namely, smoking only, smokeless tobacco use only, and both smoking and smokeless tobacco use were considered as outcomes in this study. Descriptive statistics, cross-tabulations and multinomial logistic regression analysis were adopted as analytical tools. Smokeless tobacco use was the major form of tobacco use in India followed by smoking and dual tobacco use. Tobacco use was higher among males, the less educated, the poor, and the rural population in India. Respondents lacking knowledge of health hazards of tobacco had a higher prevalence of tobacco use in each form.
Latent Class Evaluation in Educational Trials: What Percentage of Children Benefits from an Intervention?
June 08, 2020
Typically studies in education have used the standardised mean difference as a measure of the impact of interventions. This measure, commonly known as the effect size, is problematic, in terms of how it is interpreted and understood. In this study, we propose a “gain index” as an alternative metric for quantifying and communicating the effectiveness of an intervention. This is estimated as the difference in the percentage of children who make positive gains between the intervention and control groups. Analysis of four randomized controlled trials in education supports the expectation that most children make progress due to normal school activities, which is independent of the intervention.
Professional Experience
Working
December 2018 - 2021
Postdoctoral Research Associate Statistics and Associated Researcher Institute for Data Science
Durham University
Working on a research project funded by the Education Endowment Foundation (EEF) in the United Kingdom led by Durham University to support the analysis of the Education Endowment Foundation’s archive of educational trials to examine impact of different educational interventions using statistical software and to undertake the methodological exploration of the data using appropriate multilevel or bayesian models. Along with this role, I am also affiliated as a researcher in the recently established Institute for Data Science at University.
2021-Present
Assistant Professor (Research), Durham University
I am currently working as an Assistant Professor (Research) in statistics and quantitative methods in the Department of Anthropology. My research is interdisciplinary, at the crossroads of statistics, demography, and public health. My area of expertise are Quantitative Data Analysis and Methods, Biostatistics, Mathematical Demography, Mortality and Health, and multilevel analysis. I am currently handling a research project as a co-investigator for the “Methodological Research to Support Evaluation, Synthesis and Translation of Evidence to Improve the Educational Attainments of Disadvantaged Children in England” project.
November 2016- December 2018
Postdoctorate Fellow
Universite Catholique de Louvain Belgium
As a MOVE-IN Louvain postdoctorate, successfully conducted an individual project entitled “Spatial modeling of child mortality at the district level in selected states of India” with a grant from University Catholique de Louvain and co-funding by the Marie Curie Actions of the European Commission. This project pertains to application of spatial-temporal data analysis tools to the statistical modeling of child mortality at the district level in India using national-level data sources and R programming.
September 2015- October 2016
Senior Project Officer Research
International Institute for Population Sciences
LASI project is undertaken as a collaborative consortium agreement between IIPS (Mumbai), the Harvard School of Public Health, and the RAND Corporation (USA). LASI is the first large-scale longitudinal study focusing on the health, economic, and social well-being of India's elderly population. Key contribution was preparing a sampling plan and selection of sample for this longitudinal study for all states of India
Education
2011-2016
PhD in Population Studies
My Ph.D. thesis aimed to examine the improvement in survival rates in India with unconventional indicators of mortality such as the average life loss. I gained expertise in using a wide variety of large-scale population and Public Health data. and published three peer-reviewed papers in international journals and received Award of Best Ph.D. thesis.
2008-2010
M.Phil. in Population Studies
Completed Master of Philosophy in Population Studies from International Institute for Population Sciences (IIPS), Mumbai, India with Grade Point (6.74 / 10.0) and took courses on Fertility and Nuptiality, Mortality, Morbidity and Public Health, Migration, Spatial Distribution and Urbanization, Advanced Research Methodology and Biostatistics
2006-2008
Master of Science in Statistics
Graduated with Master of Science in Statistics Degree from University of Allahabad, India with aggregate 71.4%
and completed courses on Econometrics, Stochastic Processes and Time Series Analysis, Linear estimation, Design of experiments and Non-parametrics, Matrix Algebra, Multivariate Analysis, and Linear Estimation.
Get in Touch
Assistant Professor (Research)
Associated Researcher, Institute for Data Science
Durham University
Dawson Building South Road
Durham - DH1 3LE
United Kingdom
