Education, gender, and state-level disparities in the health of older Indians: Evidence from biomarker data

Using new biomarker data from the 2010 pilot round of the Longitudinal Aging Study in India (LASI), we investigate education, gender, and state-level disparities in health. We find that hemoglobin level, a marker for anemia, is lower for respondents with no schooling (0.7 g/dL less in the adjusted model) compared to those with some formal education and is also lower for females than for males (2.0 g/dL less in the adjusted model). In addition, we find that about one third of respondents in our sample aged 45 or older have high C-reaction protein (CRP) levels (>3 mg/L), an indicator of inflammation and a risk factor for cardiovascular disease. We find no evidence of educational or gender differences in CRP, but there are significant state-level disparities, with Kerala residents exhibiting the lowest CRP levels (a mean of 1.96 mg/L compared to 3.28 mg/L in Rajasthan, the state with the highest CRP). We use the Blinder–Oaxaca decomposition approach to explain group-level differences, and find that state-level disparities in CRP are mainly due to heterogeneity in the association of the observed characteristics of respondents with CRP, rather than differences in the distribution of endowments across the sampled state populations.

Allocating Participants to Groups In Educational Trials: What Does Random Mean?

What is meant by the term random? Do we understand how to identify which type of randomisation to use in our future research projects? We, as researchers, often explain randomisation to potential research participants as being a 50/50 chance of selection to either an intervention or control group, akin to drawing numbers out of a hat. Is this an accurate explanation? And are all methods of randomisation equal? This paper aims to guide the researcher through the different techniques used to randomise participants with examples of how they can be used in educational research.