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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