This SAS code adjusts weights (e.g., sample weights) such that the sum of weights equals the sample size. Weight1 is the original weight and weight 2 is the result.
proc sql; create table comp2 as select *, psweight * (count(weight1)/Sum(psweight1)) as weight2 from comp;
What works Clearinghouse considers an effect size of .25 as “substantively important” and interpreted as “qualified positive” even when the effect size is not statistically significant.
What Works Clearinghouse: Procedures and Standards Handbook (version 3.0). What Works Clearinghouse. p.23 http://ies.ed.gov/ncee/wwc/pdf/reference_resources/wwc_procedures_v3_0_standards_handbook.pdf
Mathematically, you only need the coefficient for the predictor to derive an odds ratio (you don't need the intercept value).
When describing statistical models and results in writing, the following are tricky issues and require decisions and standardized way of description (and they must be brief, intuitive, full of meaning):
How do we choose omitted category/reference group? Why is there no level-1 error term in logistic regression? Why use HLM? Why use logistic regression model? […]
The UCLA site explains Cronbach's alpha as the average internal correlation among survey items. It also says that it is not a measure of unidimensionality. Rather, it is a measurement of internal consistency (though just intuitively I feel what is coherent tends to be also uni-dimensional… I think the point is that the measure is […]
Simple random sampling given the population size
Confirm that regular regression analysis produces larger standard errors. Using the total sample size as a part of the modeling process, PROC SURVEYREG achieves smaller standard errors (more precise measurement). data IceCream; input Grade Spending Income Kids @@; datalines; 7 7 39 2 7 7 38 1 […]
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