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I have a data set representing participants in some international olympiad, it has columns gender (dummy variable), year of the olympiad, name of a person and the prize this person won. I need to estimate the following linear probability model: 1{gold_ind_i = 1} = α+β×1{d_female_i= 1}+ ∑_(j comes from 1968 to 2018)μ_j ×1{Year j = Year i}+εi
, i.e., my dependent variable is dummy depicting whether particular person received gold medal, predictors are dummy for gender (equals to 1 if a person is female) and dummy variable for each year. For instance, in year 1999 dummy for that year is equal to 1 and dummies for all other years are 0. I can run regression just on the variable gender. The problem is with including the dummies in the model associated with years since I have a large sample of these years (from 1960's to 2000's)

John P.
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    It's easier to help you if you include a simple [reproducible example](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) with sample input and desired output that can be used to test and verify possible solutions. – MrFlick Dec 13 '18 at 19:53

1 Answers1

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Found a solution: simply use "fastDummies" package.

John P.
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