Hello everyone!
I am working on a project willing to examine the diffusion of tecnology in the airplane industry.
I have data for every different commercial airplane in the market from 1957-2017. I know the build year of each plane, whether it is in use or it is retired, as well as the current age of each working plane and the eventual age of each retired plane. The survival variable takes the value 1 if the plane is in use, 0 otherwise.
I want to apply survival analysis (Cox regression) to examine how the hazard rate of each airplane is affected by some characteristics (industry, macro etc).
Do you have any idea on how to stset my data? I know that the general formula is stset time, failure(censor).
Also, I want to run (experimentally) an OLS and a logit regression. I am a little puzzled about the dependent variable of each regression.
Thank you very much!!
A sample of the data is here:
clear
input str32 Type str20 SerialNumber str42 Manufacturer double(Age AgeatRetirement) int(StatusChangeDate BuildYear) str6 Submarket byte Survival
"MD-11" "48798" "Boeing (McDonnell-Douglas)" 18.1 . 14483 1999 "Heavy" 1
"DC-8" "45264" "Boeing (McDonnell-Douglas)" . 24.4 9131 1960 "Small" 0
"L-1011 TriStar" "1046" "Lockheed Aircraft Corp" . 22.7 13300 1973 "Heavy" 0
"A330" "QTR-A330-78961" "Airbus" . . 19679 2019 "Medium" 1
"787" "BER38756" "Boeing" . . 17335 2018 "Heavy" 1
"C-135" "17811" "Boeing" 58.2 . -198 1959 "Heavy" 1
"767" "24086" "Boeing" 28.8 . 21021 1988 "Small" 1
"747" "23815" "Boeing" . 25.4 19984 1989 "Heavy" 0
"C-17" "P-24" "Boeing (McDonnell-Douglas)" 21.6 . 13174 1996 "Heavy" 1
"777" "61736" "Boeing" .9 . 20768 2016 "Heavy" 1
"747" "26559" "Boeing" 16 . 20552 2001 "Heavy" 1
"C-141" "6230" "Lockheed Aircraft Corp" . 38 16617 1967 "Large" 0
"777" "27038" "Boeing" 12.5 . 16551 2005 "Large" 1
"A330" "1693" "Airbus" 1.8 . 20437 2015 "Heavy" 1
"777" "QTR-B777-78896" "Boeing" . . 19920 2026 "Large" 1
"A350" "UAL-A350-109313" "Airbus" . . 21068 2027 "Heavy" 1
"A380" "BAW38018" "Airbus" . . 17524 2020 "Heavy" 1
"A330" "113" "Airbus" 22 . 13673 1995 "Heavy" 1
"747" "19660" "Boeing" . 31.6 15350 1970 "Heavy" 0
"A330" "889" "Airbus" 9.8 . 17519 2007 "Heavy" 1
"A330" "328" "Airbus" 17.5 . 20850 2000 "Heavy" 1
"767" "33048" "Boeing" 14.9 . 15690 2002 "Heavy" 1
"747" "21831" "Boeing" . 25.2 16608 1980 "Medium" 0
"A380" "130" "Airbus" 3.6 . 19901 2014 "Heavy" 1
"747" "20332" "Boeing" . 38.7 18423 1971 "Heavy" 0
"Il-76" "0073476281" "United Aircraft Corporation (Ilyushin)" . 20.7 17546 1987 "Heavy" 0
"777" "29324" "Boeing" 18.9 . 20788 1998 "Heavy" 1
"A300" "305" "Airbus" . 20.2 16512 1984 "Small" 0
"A300" "794" "Airbus" 18.9 . 14200 1998 "Heavy" 1
"C-135" "18149" "Boeing" . 39.1 14917 1961 "Heavy" 0
end
format %td StatusChangeDate
I am working on a project willing to examine the diffusion of tecnology in the airplane industry.
I have data for every different commercial airplane in the market from 1957-2017. I know the build year of each plane, whether it is in use or it is retired, as well as the current age of each working plane and the eventual age of each retired plane. The survival variable takes the value 1 if the plane is in use, 0 otherwise.
I want to apply survival analysis (Cox regression) to examine how the hazard rate of each airplane is affected by some characteristics (industry, macro etc).
Do you have any idea on how to stset my data? I know that the general formula is stset time, failure(censor).
Also, I want to run (experimentally) an OLS and a logit regression. I am a little puzzled about the dependent variable of each regression.
Thank you very much!!
A sample of the data is here:
clear
input str32 Type str20 SerialNumber str42 Manufacturer double(Age AgeatRetirement) int(StatusChangeDate BuildYear) str6 Submarket byte Survival
"MD-11" "48798" "Boeing (McDonnell-Douglas)" 18.1 . 14483 1999 "Heavy" 1
"DC-8" "45264" "Boeing (McDonnell-Douglas)" . 24.4 9131 1960 "Small" 0
"L-1011 TriStar" "1046" "Lockheed Aircraft Corp" . 22.7 13300 1973 "Heavy" 0
"A330" "QTR-A330-78961" "Airbus" . . 19679 2019 "Medium" 1
"787" "BER38756" "Boeing" . . 17335 2018 "Heavy" 1
"C-135" "17811" "Boeing" 58.2 . -198 1959 "Heavy" 1
"767" "24086" "Boeing" 28.8 . 21021 1988 "Small" 1
"747" "23815" "Boeing" . 25.4 19984 1989 "Heavy" 0
"C-17" "P-24" "Boeing (McDonnell-Douglas)" 21.6 . 13174 1996 "Heavy" 1
"777" "61736" "Boeing" .9 . 20768 2016 "Heavy" 1
"747" "26559" "Boeing" 16 . 20552 2001 "Heavy" 1
"C-141" "6230" "Lockheed Aircraft Corp" . 38 16617 1967 "Large" 0
"777" "27038" "Boeing" 12.5 . 16551 2005 "Large" 1
"A330" "1693" "Airbus" 1.8 . 20437 2015 "Heavy" 1
"777" "QTR-B777-78896" "Boeing" . . 19920 2026 "Large" 1
"A350" "UAL-A350-109313" "Airbus" . . 21068 2027 "Heavy" 1
"A380" "BAW38018" "Airbus" . . 17524 2020 "Heavy" 1
"A330" "113" "Airbus" 22 . 13673 1995 "Heavy" 1
"747" "19660" "Boeing" . 31.6 15350 1970 "Heavy" 0
"A330" "889" "Airbus" 9.8 . 17519 2007 "Heavy" 1
"A330" "328" "Airbus" 17.5 . 20850 2000 "Heavy" 1
"767" "33048" "Boeing" 14.9 . 15690 2002 "Heavy" 1
"747" "21831" "Boeing" . 25.2 16608 1980 "Medium" 0
"A380" "130" "Airbus" 3.6 . 19901 2014 "Heavy" 1
"747" "20332" "Boeing" . 38.7 18423 1971 "Heavy" 0
"Il-76" "0073476281" "United Aircraft Corporation (Ilyushin)" . 20.7 17546 1987 "Heavy" 0
"777" "29324" "Boeing" 18.9 . 20788 1998 "Heavy" 1
"A300" "305" "Airbus" . 20.2 16512 1984 "Small" 0
"A300" "794" "Airbus" 18.9 . 14200 1998 "Heavy" 1
"C-135" "18149" "Boeing" . 39.1 14917 1961 "Heavy" 0
end
format %td StatusChangeDate
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