Comparing regression models in R -


i need test if figures 1999-2001 period improved since 2002-2004 period. tried pooling data these 2 periods , comparing adjusted r-squares of linear regression model (e.g., lm(y~a+b)) not lead right conclusion. suppose by-company regression more relevant because regression coefficients naturally differ company company.

how can such by-firm regression in r? or there way of testing if model has become 'better fit' on 2 periods? thanks

data looks (way more companies of course):

company year    y                       b 11308   1999    -0,0208100  0,014718891 -0,006672241  11308   2000    -0,0073200  0,01513105  -0,001765405  11308   2001    -0,0242500  0,026331427 0,011924914  11308   2002    0,0071770   0,033910057 -2,55861e-05  11308   2003    -0,0161000  0,039996572 0,003413556  11308   2004    -0,0283000  0,038958565 0,004018833  11850   1999    -0,0001400  0,044492288 0,008268478  11850   2000    -0,0023400  0,057337917 0,028973756  11850   2001    -0,0113100  0,049981605 -0,002928416  11850   2002    0,0055080   0,04095854  -0,015228795  11850   2003    -0,0150000  0,089150637 0,042316779  11850   2004    0,0065680   0,093468014 0,016125354

sounds r-to-z transformation might work quite here: http://vassarstats.net/rdiff.html

this package in r can you: https://cran.r-project.org/web/packages/cocor/cocor.pdf


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