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20ModelLME - IDENTIFYING AN APPROPRIATE MODEL Given a...

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IDENTIFYING AN APPROPRIATE MODEL I Given a description of a study, how do you construct an appropriate model? I Context: more than one size of e.u. I A made-up example, intended to be complicated (but far from being the most complicated I’ve seen) I A study of the impact of micro-credit schemes in Ghana (West Africa). Micro-credit is the idea that by providing small loans, you can stimulate economic activity and bring people out of poverty and malnutrition. There are various ways this can be implemented, as giving loans, as giving loans and nutrition education, or by just giving nutrition education. Ghana has a mix of urban, suburban, and rural areas. Rainfall decreases from the coast (tropical rain forest) to semi-desert on the northern border with Burkina-Faso. Both are important blocking variables, so a Latin Square design was used. c 2011 Dept. Statistics (Iowa State University) Stat 511 section 20 1 / 15
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I Ghana was divided into four rainfall zones; in each zone an urban, a near-suburban, a far-suburban, and a rural area were identified. The three treatments and a placebo were randomly assigned to areas subject to Latin Square constraints: Rainfall zone Area Wet Wet-mid Mid Dry Urban Loan None L+N Nutr. Near Suburban None L+N Nutr. Loan Far Suburban L+N Nutr. Loan None Rural Nutr. Loan None L+N I These 16 areas are still quite large. Each area was divided into 3. I Within each 1/3’rd, one village or neighborhood was randomly chosen as the focal group. That group received the experimental treatment. I An adjacent village/neighborhood within the 1/3’rd received no treatment (control). I A somewhat distant village/neighborhood (still within the 1/3’rd) was also studied. c 2011 Dept. Statistics (Iowa State University) Stat 511 section 20 2 / 15
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I The response of interest is a measure of food security I good: have enough food I bad: ate less than one meal per day. I continuous scale derived from 15 answers to a questionaire I This is measured on randomly chosen families within each village/neighborhood.
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