@article{Hakim_Bhuiyan_Akter_Mohit_Alam_Karim_Zaman_2022, title={Weighting National Survey Data in Bangladesh: Why, How and Which weight? Weighting survey data}, volume={47}, url={https://banglajol.info/index.php/BMRCB/article/view/57769}, DOI={10.3329/bmrcb.v47i2.57769}, abstractNote={<p><strong><em>Background: </em></strong>Weighting of national survey data enables the sample to be more representative of the target population. Weighting procedure is a thorough exercise and yields several types of weights. However, considerable variation exists among authors on which weight to use leaving the researchers baffled. As a result, survey data are often used by researchers without the weights leading to erroneous conclusions. In addition, despite availability of powerful yet costly statistical software•• researchers from developing countries are mostly unable to use those due to high cost. In this article, we share our experience on weighting for recent national surveys in Bangladesh using Microsoft Excel.</p>
<p><strong><em>Objectives: </em></strong>Overall objective was to perform sample weighting of a national survey of Bangladesh using Excel. As specific objective, the study was aimed at creating different weighting variables, describe their features and identify the appropriate weight to be used for analysis.</p>
<p><strong><em>Methods: </em></strong>We generated four types of weights: the base weight calculated from probabilities of selection, and non-response adjusted, population calibration adjusted, and trimmed weights. We compared the distribution of the population by sex and age by unweighted and four types of weighted numbers. Finally, we calculated weighted means, medians, ranges, standard errors, confidence intervals, variances, multiplicative effects and design effects with these four weights. In addition, we compared the weighted prevalence of a key variable of the survey using these four weights.</p>
<p><strong><em>Results: </em></strong>We compared unweighted distribution with weighted ones and identified that weighting makes the sample distribution to conform to the target population. Among the four calculated weights, the trimmed weight had narrow standard error and variance, and smallest design and multiplicative effects. It yielded an acceptable prevalence and distribution of prevalence of mental disorder.</p>
<p><strong><em>Conclusion: </em></strong>Among the four weights, we show that the trimmed weight met all parameters of good quality and precision. We performed this complex exercise using Microsoft Excel which is largely available to researchers in Bangladesh. Therefore, we recommend using the trimmed weight for national level surveys in Bangladesh in a similar context.</p>
<p>Bangladesh Med Res Counc Bull 2021; 47(2): 118-126</p>}, number={2}, journal={Bangladesh Medical Research Council Bulletin}, author={Hakim, Ferdous and Bhuiyan, Rijwan and Akter, Mst. Khaleda and Mohit, Md. Abdul and Alam, Md. Faruq and Karim, Md. Rizwanul and Zaman, M Mostafa}, year={2022}, month={May}, pages={118–126} }