![how to read stata 12 in r how to read stata 12 in r](https://i.ytimg.com/vi/HafqFSB9x70/maxresdefault.jpg)
- #How to read stata 12 in r full#
- #How to read stata 12 in r software#
- #How to read stata 12 in r code#
#How to read stata 12 in r software#
Specialization: Software Development in R by Johns Hopkins University.Specialization: Statistics with R by Duke University.Specialization: Master Machine Learning Fundamentals by University of Washington.Courses: Build Skills for a Top Job in any Industry by Coursera.Specialization: Python for Everybody by University of Michigan.Specialization: Data Science by Johns Hopkins University.Course: Machine Learning: Master the Fundamentals by Standford.My_data <- read_excel("my_file.xlsx", na = "-")Ĭoursera - Online Courses and Specialization Data science If NAs are represented by something (example: “-”) other than blank cells, set the na argument: Case of missing values: NA (not available).My_data <- read_excel("my_file.xlsx", sheet = 2) My_data <- read_excel("my_file.xlsx", sheet = "data")
#How to read stata 12 in r code#
If you use the R code above in RStudio, you will be asked to choose a file. It’s also possible to choose a file interactively using the function file.choose(), which I recommend if you’re a beginner in R programming:.To know your current working directory, type the function getwd() in R console. The above R code, assumes that the file “my_file.xls” and “my_file.xlsx” is in your current working directory. #> F-statistic: 6.992 on 2 and 137 DF, p-value: 0.The readxl package comes with the function read_excel() to read xls and xlsx files #> lm_robust(formula = GPA_year2 ~ gpa0 + ssp, data = alo_star_men, Several examples pulled nearly from the documentation: library(estimatr)
#How to read stata 12 in r full#
Regress api00 acs_k3 acs_46 full enroll, robustĪs of April 2018 I believe you want the estimatr package, which provides a near drop in replacement for lm. The last line of code above reproduces results from Stata: use # check that the default robust var-cov matrix is HC3Ĭoeftest(lmAPI, vcov = vcovHC(lmAPI)) # robust HC3Ĭoeftest(lmAPI, vcov = vcovHC(lmAPI, "HC3")) # robust HC3 (default)Ĭoeftest(lmAPI, vcov = vcovHC(lmAPI, "HC1")) # robust HC1 (Stata default) LmAPI = lm(api00 ~ acs_k3 + acs_46 + full + enroll, data= dfAPI)Ĭoeftest(lmAPI, vcov = sandwich) # robust sandwichĬoeftest(lmAPI, vcov = vcovHC(lmAPI, "HC0")) # robust HC0 The following example that demonstrates all the points made above is based on the example here.
![how to read stata 12 in r how to read stata 12 in r](http://repec.org/bocode/e/estout/esttab011.png)
![how to read stata 12 in r how to read stata 12 in r](https://i.ytimg.com/vi/H95BHswbT3w/maxresdefault.jpg)
To reproduce the Stata default behavior of using the robust option in a call to regress you need to request vcovHC to use the HC1 robust variance-covariance matrix. The sandwich option used by Charles makes coeftest use the HC0 robust variance-covariance matrix.ģ. The default variance-covariance matrix returned by vcocHC is the so-called HC3 for reasons described in the man page for vcovHC.Ģ. However, the default variance-covariance matrices used by the two is different:ġ. Multiple R-squared: 0.8062, Adjusted R-squared: 0.8059Ĭharles is nearly there in his answer, but robust option of the regress command (and other regression estimation commands) in Stata makes it possible to use multiple types of heteroskedasticity and autocorrelation robust variance-covariance matrix estimators, as does the coeftest function in the lmtest package, which in turn depends on the respective variance-covariance matrices produced by the vcovHC function in the sandwich package. Lmrob(formula = yb7 ~ Buildsqb7 + No_Bed + Rain_Harv + Swim_Pl + Gym + Pr_Terrace, reg yb7 buildsqb7 no_bed no_bath rain_harv swim_pl pr_terrace, robust Here are the results I obtained when I ran the robust option in Stata. Can anybody please suggest something in this context? In both cases the results are quite different from the "robust" option in Stata. I have used the rlm command form the MASS package and also the command lmrob from the package "robustbase".
![how to read stata 12 in r how to read stata 12 in r](https://i.ebayimg.com/images/g/ePoAAOSwLt5espnS/s-l400.jpg)
I have been trying to replicate the results of the Stata option robust in R.