This is the paper - https://pubmed.ncbi.nlm.nih.gov/12096871/

This is the bit I'm most confused by - “Both the remaining variables—log frequency and log density— showed significant contributions to the model p <.001, so no further steps were taken. In the resulting model, the two variables together made a significant contribution in accounting for the error rates (F(2172) =29:72, p <:001)”

Whole paragraph for context:

"The aim of the regression analysis was to reveal which of these variables appear to be the most important predictors of naming accuracy. Because of the missing neighborhood frequency values for zero-density items, this variable was excluded so that the regression analysis could be conducted on the full set of PNT stimuli, but the correlations described above suggest that the exclusion of neighborhood frequency does not sacrifice much predictive power from the regression model. Thus, the log- transformed error rates were regressed on the log values of item frequency and neighborhood density and on the number of syllables of each item. In the original model, the three variables together accounted for 26.0% of the variance in error rates (R = .510). In the next step, the variable contributing the least amount to the model—number of syllables—was removed, with negligible change in the overall R (from .510to .507). Both the remaining variables—log frequency and log density— showed significant contributions to the model (p <.001), so no further steps were taken. In the resulting model, the two variables together made a significant contribution in accounting for the error rates (F(2172) = 29:72, p <:001); however, it should be noted that they still accounted for only about 26% of the variance in PNT accuracy. It seems logical that this reflects the influence of other factors on naming accuracy, since the error rate used in the analysis includes other types of errors, such as semantic errors, descriptions, and no responses."