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Dear R-users, I have a dataset as like below, and I want to subtotal the values of rice,wheat and maize by year for each fid. fid      year     rice     wheat      maize ------------------------------------------------ 1        1995      5        NA           NA 1        1995      NA        3           NA 1        1995      NA       NA           2 1        1996      4        NA           NA 1  

Hello R-users,   The below is a snippet of my data:   fid crop year value 5_1_1 SWHE 1995 171 5_1_1 SWHE 1997 696 5_1_1 BARL 1996 114 5_1_1 BARL 1997 344 5_2_2 SWHE 1995 120 5_2_2 SWHE 1996 511 5_2_2 BARL 1996 239 5_2_2 BARL 1997 349   Here, I want to create dummy variables with the names of the content of a column 'crop' in a way

Dear R Users, I am a novice learner of R software. I am working with Genetic Matching - GenMatch(), but I am getting an Error message as follows:  Error in GenMatch(Tr = Tr, X = X.binarynp, BalanceMatrix = BalanceMatrix.binarynp,  :    GenMatch(): input includes NAs Could you please suggest me correcting the above problem? My GenMatch command is, > gen1 <- GenMatch(Tr = Tr, X =

Dear R Users, I am a novice learner of R software. I am working with Genetic Matching - GenMatch(), but I am getting an Error message as follows:  Error in GenMatch(Tr = Tr, X = X.binarynp, BalanceMatrix = BalanceMatrix.binarynp,  :    GenMatch(): input includes NAs Could you please suggest me correcting the above problem? My GenMatch command is, > gen1 <- GenMatch(Tr = Tr, X =

Dear R users, Is it possible to apply 'predict' to an object of class "conmode"?  Could you please suggest me any applicable method for 'predict' for the "conmode" class? Thanking you, Sincerely Yours, Shyam Kumar Basnet SLU, Uppsala Sweden [[alternative HTML version deleted]]

Dear R-Users, I have a problem on extracting T-Stat and P-Value. I have written R-code below library("Matching") data("lalonde") attach(lalonde) names(lalonde) Y <- lalonde$re78 Tr <- lalonde$treat glm1 <- glm(Tr~age+educ+black+hisp+married+nodegr+re74+re75,family=binomial,data=lalonde) pscore.predicted <- predict(glm1) rr1 <-