It would help if you can not readily do multilevel modeling with a 4 point DV to know what can analyze this. I am testing the result of area on satisfaction.

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It would help if you can not readily do multilevel modeling with a 4 point DV to know what can analyze this. I am testing the result of area on satisfaction.

Ok I have a different question. OLS regression is very common including among academicians. But MLM modeling argues essentially that if something can be nested inside something else then they will generate errors. That is the chance of getting a type 1 or type 2 error is much greater. My question is how you know when this is a problem or not. They do linear regression in my area (vocational rehabilitation) yet virtually all data is going to be nested (customers inside units inside areas).

How do you know if the linear method is valid in this case, as compared to having to use multilevel models. I am not sure statistical test are valid period in honesty because I usually have at least 60 percent of the data and often 100 percent.

To make things more confusing to me what I am interested in is the nesting inside areas. There are only 7 of these. Based on this comment I am not sure it is even valid to analyze this few groups with multilevel data.

"Guidelines for sample-size requirements and their implications for model complexity, the regression coefficients, variance components, and their standard errors are given in various studies and texts. For example, models with fewer than 20–25 groups may not provide accurate estimates of the regression coefficients and their standard errors, or of the variance components and their standard errors."

https://ies.ed.gov/ncee/edlabs/regions/northeast/pdf/REL_2015046.pdf

I do have a lower level called units, but no one cares about units and there are issues because some units overlap each other while being administrative separate.

How do you know if the linear method is valid in this case, as compared to having to use multilevel models. I am not sure statistical test are valid period in honesty because I usually have at least 60 percent of the data and often 100 percent.

To make things more confusing to me what I am interested in is the nesting inside areas. There are only 7 of these. Based on this comment I am not sure it is even valid to analyze this few groups with multilevel data.

"Guidelines for sample-size requirements and their implications for model complexity, the regression coefficients, variance components, and their standard errors are given in various studies and texts. For example, models with fewer than 20–25 groups may not provide accurate estimates of the regression coefficients and their standard errors, or of the variance components and their standard errors."

https://ies.ed.gov/ncee/edlabs/regions/northeast/pdf/REL_2015046.pdf

I do have a lower level called units, but no one cares about units and there are issues because some units overlap each other while being administrative separate.

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"Traditionally, researchers tended to use model results at one level to draw statistical inference at another level [individual to group]. This has proven incorrect. The results from the two single level models frequently differ either in magnitude or in sign. The relationships found at the group level are not reliable predictors for relationships at the individual level. "

Individual variables are variables that operate at the individual level, group variables operate at a higher level like a school. So my question would be, ignoring wrong SE which can be dealt with by robust SE, can you run OLS with variables where some variables are nested inside others like person in school. I know this is done a lot - formally it violates independence. But does it seriously bias the results?

And if it does does this mean all OLS with a variable that can be placed in a hierarchy is wrong?

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