Level identification for repeated measures
Posted: Wed May 05, 2021 10:22 am
Hi,
I wonder if there is a
I am currently working on study that aims to investigate how physical activity level (predictor) is related to sleep duration (outcome) in adolescents (n=92). We have tracked students for seven days (i.e. we have 7 measurements for each subject for every variable) which makes this study a study with a repeated measures design. Also, students are clustered within the classes (n=68) within the schools (n=4). Physical activity level, sleep duration, and other confounding variables are continuous.
My questions are following:
1. Do I have 4-level structured data (i.e. measurements at L-1; students at L-2; classes at L-3; and schools at L-4) ?
2. Can I statistically compare models at level-1 (which includes measurements) with models at level-2 (wich includes measurements and students) to see where is more clustering?
3. Does L-1 variable (i.e. measurements) is set in mlwin in the same way as other ''typical'' variable of interest (e.g. student at L-1)?
4. Which 'statistical approach' is best for these kind of structured data?
Thanks
Josip
I wonder if there is a
I am currently working on study that aims to investigate how physical activity level (predictor) is related to sleep duration (outcome) in adolescents (n=92). We have tracked students for seven days (i.e. we have 7 measurements for each subject for every variable) which makes this study a study with a repeated measures design. Also, students are clustered within the classes (n=68) within the schools (n=4). Physical activity level, sleep duration, and other confounding variables are continuous.
My questions are following:
1. Do I have 4-level structured data (i.e. measurements at L-1; students at L-2; classes at L-3; and schools at L-4) ?
2. Can I statistically compare models at level-1 (which includes measurements) with models at level-2 (wich includes measurements and students) to see where is more clustering?
3. Does L-1 variable (i.e. measurements) is set in mlwin in the same way as other ''typical'' variable of interest (e.g. student at L-1)?
4. Which 'statistical approach' is best for these kind of structured data?
Thanks
Josip