data WORK.ANALYTIC;
infile datalines dsd truncover;
input fips:$7. year:32. ptb:32. entropyindex:32. mua:32. rural:32.;
datalines;
01001 2007 15.4 0.6408070774 1 0
01001 2008 14.9 0.6347032529 1 0
01001 2009 14.6 0.5946361175 1 0
01001 2010 13.6 0.4998764511 1 0
01001 2011 13.7 0.4841341568 1 0
01001 2012 13.5 0.4451194338 1 0
01001 2013 13.2 0.4636948987 1 0
01001 2014 11 0.5613597794 1 0
01001 2015 10.5 0.4616523638 1 0
01001 2016 10.6 0.5859625243 1 0
01001 2017 10.2 0.5429811399 1 0
01001 2018 11.3 0.7012052158 1 0
01001 2019 11.9 0.5924427314 1 0
01003 2007 16.3 0.5890522164 1 0
01003 2008 15.6 0.6327763934 1 0 Hello, I am trying to look at the relationship between my exposure variable (ptb) and outcome variable (entropyindex) over the time period 2007-2019 for every county in the US (each county has a unique "fips" code). There are over 3,000 counties each year. Additionally, I have two covariates - mua and rural. A snippet of my data is provided above. For data structured this way, would the best way to run a time series analysis be to use proc varmax? Please let me know if I can provide any additional information!
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