Hello everybody,
I used predicted variables from PCA for an EFA and want to implement my findings (11 factors) in a probit model.
What I did so far and what is planned:
I am somewhat stuck on how to implement the probit model.
I did use "predict fa1 fa2 ... fa11" to get the new variables from my factor I found via the FA. Through "mkmat...., mat(probitraw) obs nchar(1)", "mat probitfa = probitraw*fa" and "svmat probitfa, names( col )" I was able to implement the structure / factors onto my new set 3.
Now running probit on the list of variables found via this, plus some extra dummy variables, seems to have a problem.
It shows:
outcome does not vary; remember:
0 = negative outcome,
all other nonmissing values = positive outcome
From my research it apparently comes from an incorrect implementation of binary variables, but they seem to be fine.
Here my results from my "summarize $probitlist"
Can someone help?
Thank you in advance!
Aaron
I used predicted variables from PCA for an EFA and want to implement my findings (11 factors) in a probit model.
What I did so far and what is planned:
- I cut my dataset into 4 sets
- I used PCA to trim down from my ~180 variables (I now have 48 items and 9 components describing those)
- I used these 9 components and implemented them into my second set for an EFA
- After finding the underlying structure of 11 factors, I want to implement these findings on a third set to regress a probit model
- The last set of the 4 is for running the probit model.
I am somewhat stuck on how to implement the probit model.
I did use "predict fa1 fa2 ... fa11" to get the new variables from my factor I found via the FA. Through "mkmat...., mat(probitraw) obs nchar(1)", "mat probitfa = probitraw*fa" and "svmat probitfa, names( col )" I was able to implement the structure / factors onto my new set 3.
Now running probit on the list of variables found via this, plus some extra dummy variables, seems to have a problem.
It shows:
outcome does not vary; remember:
0 = negative outcome,
all other nonmissing values = positive outcome
From my research it apparently comes from an incorrect implementation of binary variables, but they seem to be fine.
Here my results from my "summarize $probitlist"
Variable | Obs | Mean | Std. Dev. | Min | Max |
size_fin_fa | 456 | 2.39e+07 | 9.67e+07 | 64475.97 | 1.10e+09 |
impactpwor~a | 456 | -304119.8 | 7107358 | -1.10e+08 | 5.35e+07 |
opexratio_fa | 456 | -13441.49 | 528577.8 | -4858843 | 7785143 |
nparatio_fa | 456 | -4174440 | 1.80e+07 | -1.90e+08 | -12590.47 |
size_emp_fa | 456 | 2403224 | 1.40e+07 | -3218961 | 2.23e+08 |
risk_fa | 456 | -3355884 | 1.65e+07 | -2.56e+08 | 408332 |
opincmargi~a | 456 | -2767453 | 1.30e+07 | -1.80e+08 | 2.62e+07 |
nonintincm~a | 456 | -435768.6 | 5186972 | -8.96e+07 | 2.36e+07 |
netloanrat~a | 456 | 4631591 | 1.80e+07 | -1125717 | 1.72e+08 |
netincrati~a | 456 | 6312471 | 2.77e+07 | -1.11e+08 | 3.19e+08 |
roe_fa | 456 | -538707.7 | 1.14e+07 | -1.03e+08 | 1.37e+08 |
usa | 456 | .9166667 | .276689 | 0 | 1 |
bank_based | 456 | .0526316 | .2235421 | 0 | 1 |
market_based | 456 | .004386 | .0661538 | 0 | 1 |
eastern_eu~e | 456 | .0153509 | .123079 | 0 | 1 |
outliers | 456 | .002193 | .0468293 | 0 | 1 |
interconti~l | 456 | .0065789 | .0809322 | 0 | 1 |
bank_type | 456 | .0504386 | .2190886 | 0 | 1 |
Can someone help?
Thank you in advance!
Aaron
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