RMSM Code

Stata code accompanying “Building an Empirical Body of Evidence: Developing Rapport with Reviewers and Overcoming Skepticism in Strategic Management Research,” in Research Methodology in Strategy and Management, Volume 15. (Paper)

Appendix 1. Random data regressions

---

clear
//set the number of observations
set obs 1000

//create a variable in dataset to capture betas, p-values, and confidence interval
gen b = .
gen p = .
gen ci_l = .
gen ci_h = .

//loop from 1 to 100
forvalues i = 1/100 {
    gen y`i' = rnormal()            //generate y1 through y100
    gen x`i' = rnormal()            //generate x1 through x100
    reg y`i' x`i'                   //run regression predicting y_i with x_i
    mat b = r(table)                //save results table
    replace b    = b[1,1] if _n==`i'   //b-value of the i-th model, saved to i-th row
    replace p    = b[4,1] if _n==`i'   //p-value
    replace ci_l = b[5,1] if _n==`i'   //low side of confidence interval
    replace ci_h = b[6,1] if _n==`i'   //high side of confidence interval
}

//count how many p-values are <= 0.05
count if p<=.05

Appendix 2. Outlier example

---

clear
set obs 100
gen y = rnormal()
gen x = rnormal()
reg y x                 //significant at p <= 0.05 about 1 in 20 times

set obs 104             //add 4 more observations to the data

//generate the 4 outliers
replace y =  2.5 in 101
replace x =  2.5 in 101
replace y = -3.0 in 102
replace x = -3.5 in 102
replace y =  3.5 in 103
replace x =  3.0 in 103
replace y = -2.5 in 104
replace x = -2.5 in 104

reg y x                 //significant at p <= 0.05 nearly every time
scatter y x