I am a beginner in statistics and poor in mathematics. I am trying to to assess effect of intervention in one state versus another using annual data.
My data are
State 1 State 2
Cases Deaths Cases Deaths
2004 1125 5 2024 254
2005 1213 5 1978 209
2006 1003 4 2294 217
2007 1425 6 2312 249
2008 1172 4 1528 197
2009 1092 3 1683 204
2010 1316 4 2024 218
When I was stuck for the correct statistical procedure, one senior member "irishstat" advised me the following very convincing analysis for which I am ever grateful: X1 is the number of cases and Y is the number of deaths. X2 is the empirically identified point of anomaly; (2009 .. period 6 for State1 and 2004 .. period 1 for State2. Outlier detection led to identifying one anomalous data point for each state reflecting some unknown background variable thus yielding a more robust estimate of the mortality rates.
Analysis of State1
State1 Y(T) = -.65649
+[X1(T)][.0046)] CASES +[X2(T)][-1.3608)] PULSE6 I~P00006STATE1 + [A(T)]
Suggesting an unusually low mortality rate for 2009
Analysis of State2
State2 Y(T) = 123.55
+[X1(T)][(+ .0468)] CASES +[X2(T)][(+ 35.7590)] PULSE1 I~P00001STATE2 + [A(T)]
Suggesting an unusually high mortality rate for 2004
This leads to estimating two cleansed data points
STATE YEAR Y OBSERVED Y ADJUSTED
STATE1 2009 3 4.36
STATE2 2004 254 218.24
Replacing these two observed possibly errant values possibly due to some unspecified concomitant factor (“lurking Variable”) one computes a rate of.0046 for STATE1 and .0468 for STATE2. My problem now is how to do The Chow Test for constancy of parameters across groups to check for rejection of the null hypothesis of equal coefficients. I have SPSS v19. Kindly advise me step by step.