The Journal of College and University Student Housing - Volume 43, No. 1 - 50

Maureen E. Wilson * Amy S. Hirschy * John M. Braxton

surveys from undergraduate resident advisors
and 320 incomplete surveys were excluded
from data analysis, so ﬁndings are based on
972 responses, 8.6% of the sample. Demographic characteristics of the sample are displayed in Table 1.
Although the number of responses is
large, the response rate is rather low, raising
concerns about how well the sample represents the population. To assess the effects of
response bias, we conducted a mailing wave
analysis. According to Leslie (1972), survey
respondents who complete the survey later in

and the ﬁnal reminder email. Of the ﬁve variables, only race/ethnicity was signiﬁcant [X 2
(6, N = 962) = 18.17, p < .01)], suggesting that
HRLPs of color may be underrepresented in
the sample. T-tests on the ﬁve admonitory
norms were used to compare participants who
responded after the ﬁrst mailing to those after
the third mailing. With the noted exception
of race/ethnicity, no signiﬁcant differences
between the response groups were found.
Thus, we have a high degree of conﬁdence that
the respondents were reasonably representative of non-respondents (i.e., the ACUHO-I
population).

Limitations

Informal rules or norms among
group members comprise
normative structures to guide
professional behaviors.

the data collection timeframe are more similar
to non-respondents than early respondents.
Thus, if responses from initial participants
differ signiﬁcantly from later participants,
the data may be biased against those who did
not ﬁll out the survey, offering evidence that
the sample does not represent the population
well. To do this, we ﬁrst conducted crosstabs
on each of the four personal characteristic
variables (gender, race/ethnicity, education
level, years of HRL experience) and institutional type (four-year private, all others), comparing the ﬁrst and third waves of completed
surveys, based on the initial survey invitation
50

First, the behaviors included in the HRLBI
do not capture all possible behaviors that may
meet normative criteria. Second, although
the sample size is robust, the response rate is
low. Black/African American and Hispanic/
Latino/a professionals may be underrepresented, and therefore may not fairly represent
the population. ACUHO-I could not provide a
detailed demographic proﬁle of members so
we cannot accurately estimate the potential
sample bias. This concern is mitigated by the
mailing wave analyses in which we detected
little bias.

FINDINGS
To address the ﬁrst research question, we analyzed data using descriptive and inferential
statistics. Mirroring other studies on normative structures (e.g., Hodum & James, 2010),
items with mean scores between 3.0 and 3.99
were designated admonitory norms. Twentysix items fell in this category. Fifty-four items
had mean scores between 4.0 and 5.0 and
were labeled inviolable norms (Hirschy et al.,

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The Journal of College and University Student Housing - Volume 43, No. 1

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