r - Unprecise p-values in Stargazer -

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I want the same sitar for importance in regression output in stargazer as "normal output".

I produce data 

  Library ("Sturgers"); Library ("lmtest"); Library ("sandwich") set.seed (1234) df & lt; - data.frame (y = 1001: 1100) df $ x & lt; - c (1: 70, -100: -71) + rnorm (100, 0, 74.8) model and lieutenant; - LM (log (y) ~ x, data = df)   
 Get some model estimates where the coefficient at x is P-value of 0.1023    Coeftest (model, vcov = vcovHC (model, type = "HC3"))   
 Based on the same function I want to make these results in latex, I have standard projections corresponding to heterosacicistic stability I calculate and use Sturgers to do them.  
  stderr_HC3_model & lt; - Stringer is a star on the coefficient of output, which means alpha - (sqrt) = 10%. I want sturgers to be treated as co-feet. (Due to comparisons with Stata, where LD LE X, VCA (HC3) gives absolutely accurate results.)  
 I have a stargazer option around p.auto, t.auto which did not help Was played with. When I perform "Stargazer" I can not see the underlying code because it is possible in other cases.  
 
 Richards's response helped me, I indicate the steps of which I call more than one regression (let's Olsse and Oll-B).  
  ses & lt; - list (coeftest (ols_a, vcov = vcovHC (ols_a, type = "HC3")), [2], coffee (olsb, vcov = vcovHC (ols_b, type = "hc3")) [, 2]) yellow And LT; - List (coffeestest (OLASLA, VCOV = VCOVHC (OLSLA), type = "), [4], coeftest (ols_b, vcov = vcovHC (ols_b, type =" HC3 ")), [4] stargazer (ols_a, Ols_b, type = "text", p = pvals, se = ses) << Code>   
 
 
 Your  coeftest  from the man page.  
 
 A list of numerical vectors that will change the default P-value for each model is matched to the name of the element.  
  test & lt; - coeftest (model, vcov = vcov hc (model, etc.) type = "hc3") ses & Lt; - Test [, 2] Private & Lt; - Test [, 4] Sturgers (Model, Type = "Text", P = Poles, = SES from)   
 Provides.  
  ==================================== =========== Dependent variables: ------------------------- Log (Y) ------- ---------------------------------------- X-0.00005 consecutive 6.956 *** (0.003 ) ----------------------------------------------- Inspection 100 R2 0.026 adjusted R2 0.016 residual class error 0.027 (DF = 98) F statistical 2.620 (DF = 1; 98) ============================================== NOTE : * P & lt; 0.1; ** P & LT; 0.05; *** p & lt; 0.01

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