Do you include design weights in a multilevel model?

Do you include design weights in a multilevel model?

If including design weights in MLM, analysts should scale the weights and use software that properly includes the scaled weights in the estimation. Multilevel models (MLM) offer analysts of large scale, complex survey data a relatively new approach to understanding individual and contextual influences on public health.

How are complex survey data used in multilevel modeling?

EXAMPLES: MULTILEVEL MODELING WITH COMPLEX SURVEY DATA. Complex survey data refers to data obtained by stratification, cluster sampling and/or sampling with an unequal probability of selection. Complex survey data are also referred to as multilevel or hierarchical data. For an overview, see Muthén and Satorra (1995).

How are multilevel models used in public health?

Multilevel models (MLM) offer complex survey data analysts a unique approach to understanding individual and contextual determinants of public health. However, little summarized guidance exists with regard to fitting MLM in complex survey data with design weights.

How are design weights used in MLM estimation?

Yet, until recently, few guidelines existed for incorporating design weights into multilevel models. Second, software programs have only begun to correctly include design weights in MLM estimation. Third, little work with empirical (as opposed to simulated) data has compared and contrasted different methods for handling design weights.

Where can I learn more about multilevel models?

For more discussion of multilevel models, including principles, software, and applications, see the Multilevel Models Project. In particular, there are links to home pages for the various software packages, and some more introductory discussion. The following are tutorial introductionsto hierarchical modeling for practitioners:

How to fit MLM to complex survey data?

However, little summarized guidance exists with regard to fitting MLM in complex survey data with design weights. Simulation work suggests that analysts should scale design weights using two methods and fit the MLM using unweighted and scaled-weighted data.

When to use Student Senate weight in multilevel modeling?

Student Senate weight is used when analyses involve more than one country because it is total student weight scaled in such a way that all students’ senate weights sum to 500 (or 1000) in each country. School weight should be used when analyzing school-level data, as it is the inverse of the probability of selection for the selected school.

When to use design and population size weights?

When comparing data from two or more countries but without reference to the average (or combined total) of those countries, only the design weight need be applied. When comparing data of two or more countries and with reference to the average (or combined total) of those countries, both design and population size weights should be applied.