  Percentiles are statistics pointing to the standing of a paper's citation
impact relative to other papers in a given citation distribution. Percentile
Ranks (PRs) often play an important role in evaluating the impact of scholars,
institutions, and lines of study. Because PRs are so important for the
assessment of scholarly impact, and because citation practices differ greatly
across time and fields, various percentile approaches have been proposed to
time- and field-normalize citations. Unfortunately, current popular methods
often face significant problems in time- and field-normalization, including
when papers are assigned to multiple fields or have been published by more than
one unit (e.g., researchers or countries). They also face problems for
estimating citation counts (CCs) for pre-defined PRs (e.g., the 90th PR). We
offer a series of guidelines and procedures that, we argue, address these
problems and others and provide a superior means to make the use of percentile
methods more accurate and informative. In particular, we introduce two
approaches, CP-IN and CP-EX, that should be preferred in bibliometric studies
because they consider the complete citation distribution. Both approaches are
based on cumulative frequencies in percentages (CPs). The paper further shows
how bar graphs and beamplots can present PRs in a more meaningful and accurate
manner.
