1. Enter unadjusted p-values as a vector

I copied and pasted these from Table 3 in your manuscript.

pvalues <- c(0.00032,
             0.00023,
             0.035,
             0.023,
             0.034,
             0.00098,
             0.0013,
             0.127,
             0.838,
             0.475,
             0.343,
             0.00043,
             0.109,
             0.129,
             0.165)

labels <- c("Competency/Knowledge base (Positively Mentioned)",
"Thoroughness (Positively Mentioned)",
"Thoroughness (Negatively Mentioned)",
"Temperament (Negatively Mentioned)",
"Cost-consciousness (Negatively Mentioned)",
"Interactions with staff (Positively Mentioned)",
"Interactions with staff (Negatively Mentioned)",
"Billing and insurance (Positively Mentioned)",
"Parking (Negatively Mentioned)",
"Black",
"Other",
"Knew Name of Provider (Yes, Reference = No)",
"Responded to comments (Yes, Reference = No)",
"Practice Type (Academic, Reference = Non-academic)",
"Constant")

2. Use p.adjust function to adjust p-values

The default method is the “Holm” method. According to the R documentation: “There seems no reason to use the unmodified Bonferroni correction because it is dominated by Holm’s method, which is also valid under arbitrary assumptions.”

adj.pvalues <- p.adjust(pvalues, method = "holm")

We can compare the unadjusted with the adjusted values as follows. The changed column indicates which p-values are no longer significant (at 0.05 level) after adjustment.

changed <- ifelse(pvalues < 0.05 & adj.pvalues > 0.05, "X", "")
d <- data.frame(pvalues, adj.pvalues, changed)
row.names(d) <- labels
d
##                                                    pvalues adj.pvalues changed
## Competency/Knowledge base (Positively Mentioned)   0.00032     0.00448        
## Thoroughness (Positively Mentioned)                0.00023     0.00345        
## Thoroughness (Negatively Mentioned)                0.03500     0.30600       X
## Temperament (Negatively Mentioned)                 0.02300     0.23000       X
## Cost-consciousness (Negatively Mentioned)          0.03400     0.30600       X
## Interactions with staff (Positively Mentioned)     0.00098     0.01176        
## Interactions with staff (Negatively Mentioned)     0.00130     0.01430        
## Billing and insurance (Positively Mentioned)       0.12700     0.76300        
## Parking (Negatively Mentioned)                     0.83800     1.00000        
## Black                                              0.47500     1.00000        
## Other                                              0.34300     1.00000        
## Knew Name of Provider (Yes, Reference = No)        0.00043     0.00559        
## Responded to comments (Yes, Reference = No)        0.10900     0.76300        
## Practice Type (Academic, Reference = Non-academic) 0.12900     0.76300        
## Constant                                           0.16500     0.76300

References

Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 6, 65–70. https://www.jstor.org/stable/4615733.