  We study relationship between peer assessment of quality of U.S. Computer
Science (CS) doctoral programs and objective measures of research strength of
those programs. In Fall 2016 we collected Google Scholar citation data for
4,352 tenure-track CS faculty from 173 U.S. universities. The citations are
measured by the t10 index, which represents the number of citations received by
the 10th highest cited paper of a faculty. To measure the research strength of
a CS doctoral program we use 2 groups of citation measures. The first group of
measures averages t10 of faculty in a program. Pearson correlation of those
measures with the peer assessment of U.S. CS doctoral programs published by the
U.S. News in 2014 is as high as 0.890. The second group of measures counts the
number of well cited faculty in a program. Pearson correlation of those
measures with the peer assessment is as high as 0.909. By combining those two
groups of measures using linear regression, we create the Scholar score whose
Pearson correlation with the peer assessment is 0.933 and which explains 87.2%
of the variance in the peer assessment. Our evaluation shows that the highest
62 ranked CS doctoral programs by the U.S. News peer assessment are much higher
correlated with the Scholar score than the next 57 ranked programs, indicating
the deficiencies of peer assessment of less-known CS programs. Our results also
indicate that university reputation might have a sizeable impact on peer
assessment of CS doctoral programs. To promote transparency, the raw data and
the codes used in this study are made available to research community at
http://www.dabi.temple.edu/~vucetic/CSranking/.
