[R-sig-ME] Question on hierarchical nature and data format using lmer
thierry@onkelinx @ending from inbo@be
Tue Jun 26 10:37:55 CEST 2018
The typical format is one row of data per observation. If you have one
measurement per student, then you need to have a column per clinical
placement (with a TRUE or FALSE value).
ir. Thierry Onkelinx
Statisticus / Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx using inbo.be
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not ensure that a reasonable answer can be extracted from a given body
of data. ~ John Tukey
2018-06-25 17:09 GMT+02:00 Bernard Liew <B.Liew using bham.ac.uk>:
> Dear Community,
> Thank you first for the help. My question pertains to a research design as follow:
> 200 students in total from 4 schools, undergoing different clinical placements in a semester. There are 5 different plausible clinical placements. This means some students have zero placements, others can have a maximum of three, with any placement combinations. Two out of three clinical placements are restricted to some schools. So some clinical placements are nested within schools, others are crossed across schools.
> The response variable is an ordinal measure Likert scale of "sharing". The predictors are school and placement.
> Qn to be answered: Does different school and clinical placement alter a student's degree of sharing?
> Problem 1: data format
> The traditional way to format the data is the long "tidy" method. However, because placements are not unique to an individual, how best should one format the data?
> Solution 1 ( I think): make the placement variable into a wide format, so instead of one placement predictor, I now have five different placement predictors. This then appears to change the research question? Is there another solution?
> Kind regards,
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