ONLINE APPENDIX
A. Causal Ordering of the Study Variables
B. Novel Methodology & Reporting Statistical Results
C. Census Data Collection – Recruitment Procedures
D. Combined Theology-Polity Variable
E. Scaled vs. Raw HIV Programming Data
F. Description of the Black Protestant Group
A. Causal Ordering of the Study Variables (see Figure A1 below)
We hypothesize that theology-polity affects the location of the congregation and, in turn,
location affects the congregation’s size and demographic composition. Imagine for a moment
that an individual or group has to decide where to worship. It parallels an economic decision
concerning location choice. The decision would consider the “demand” for the theology-polity
potentially proffered by a location and its constituent population. Thus, theology-polity of the
(potential) congregation affects location. The logic is similar if the theology-polity is located,
but lacks fit with its human ecology (perhaps because of changing community conditions over
time). Viewed from this perspective, the congregation makes decisions within the constraints of
present and anticipated social conditions. The congregation decision makers, with their
theology-polity, would consider its potential for survival in their current and competing locations
and either stay or move. As for theology-polity and location affecting the size and demographic
composition of a congregation, the reasoning that – independent of location, a congregation’s
Size
(Average
Attendance)
TheologyPolity1
Location
(Urban vs
Suburban)
SocioDemographics
(Composition):
Age
Race
Education
Family Type
Operational
Resources:
Paid Clergy
& Staff
Worship Site
Changed Site
Years Existed
Religious/
Worship
Activity
(Number of
Weekly
Worship
Gatherings)
Service/Community
Work:
Spiritual Counseling
General Service
Health Programs
(non-HIV)
Handicap Access
Guest Speakers
HIV
Programs /
Services:
Education /
Prevention
Counseling
Testing
Figure A1. Path diagram of relationships between congregational theology-polity and
HIV prevention/counseling programs
belief system and organization appeals to and attracts members to differing degrees and of
certain types and thus determines the size and demographic composition of the congregation – is
so well-documented as to have attained the status of conventional wisdom in the sociological
study of religion. Similarly, there is an overwhelming body of literature that corroborates that
central city and suburban locations affect the size and composition of their populations via
constraining a surrounding population’s decisions regarding where to move. In turn, the size and
composition of a location’s population becomes the market that theology-polity congregations
penetrate to varying degrees; of course, some theology-polity types are more niche-oriented than
others.
There is no clear guidance from the literature on the causal ordering of the variables of
interest, and one may feel pushed to use these variables as correlates versus predictors. The
purpose of causal models is to test hypotheses about the causal ordering of variables. In our
study, we test a prediction of theology/polity determining congregation’s location and
sociodemographic composition, and we open a way for others to test other hypotheses about the
relationship between these variables.
B. Novel Methodology & Reporting Statistical Results
This analysis involves compromises in testing alternative hypotheses about the causal
ordering of variables, but at the same time, it constitutes a substantial methodological advance.
Path analysis generally relies on coefficients from ordinary least squares (OLS) regressions (or
coefficients that have the sense of OLS estimates, but estimated based on other statistical
procedures, such as maximum likelihood estimation). While correctly presented here in a role
subsidiary to the theoretical ideas, we developed and used a method of combining results from a
variety of regression models. The procedure allows combining results of regression procedures
that produce better estimates of effects at the various steps in the sequence of variables – e.g.,
binary, ordinal, and multinomial logistic regressions, Poison and negative binomial regressions,
and OLS regressions – to test direct and indirect effects with intuitively meaningful, comparable
coefficients. Also, because of these complexities, we do not present the results for each path
implied by the model. Rather we present a parsimonious version of the findings, focusing on the
effects of theology-polity on HIV programming. This can be viewed as a triage approach that
underscores the priority of the mediators.
This paper makes an important, innovative methodological contribution to structural equation
modeling (SEM) by expanding the capability of path analysis so that theory testing can address
causal models involving more than only OLS regressions. The strength of path analysis is that it
yields information on how 2 variables are related by partitioning their covariance (correlation)
into spurious, direct, and indirect effects. In general, the indirect effects are most informative.
These are the antecedent variable of interest effects on a dependent variable of interest that are
hypothesized to occur through specific mediating variables. The tests of these mediating effects
are explicit tests of hypothesized causal mechanisms. They make path analysis a highly
sophisticated procedure and a basic component of articulated SEM. However, an indirect effect
involves manipulating coefficients from at least 2 equations. In general, a particular path
operating through 1 or more mediating variables is statistically significant if all the coefficients
involved in path’s steps are statistically significant. Again, each coefficient on the path’s steps
come from different equations. Any indirect effect involves at least 2 test statistics and 2 p
values. The “summary” or “triage” method presented in this paper involves combining
information from 2 equations. However, there are added complications due to the complexity of
the phenomena being studied. One notable complexity is the 6-category typology making up
theology/polity. As with any categorical predictor in regression models, a nominal variable
requires [(n*(n-1))/2] paired comparisons to establish the statistically significant differences
between 2 categories; in this case, 15 paired comparisons – giving rise to Table 4’s 15 boxes
marking failure to reject the null, null-rejected 2-tailed test, and null-rejected 1-tailed test (alpha
= .05) for each effect of theology/polity on HIV programming explored (and presented in Table
3), except those operating through the sociodemographic composition of congregations. These
tests are accomplished by rotating 1 “reference category” to be omitted from a run of the
equation; thus, these 15 tests required running 5 versions of the same equation. The
sociodemographic composition variables were more complex because the influence of theologypolity on each dimension of composition required multinomial logistic regressions that produced
2 equations and required an additional run to complete significance comparisons among 3
categories. These comparisons were nested within the 5 versions of equations necessary to test
theology-polity type differences. The upshot is that many test statistics were examined and their
presentation would require many tables and make the work less comprehensible. A statistician
can follow the logic of the procedure and, with experience in path analysis with categorical
variables and with multinomial logistic regression, will know that the number of test statistics
examined will be numerous. Although not a quick read, researchers should be able to follow
how the numbers presented are arrived at and only need to take on faith that we have not erred in
looking at p values in our output from runs.
C. Census Data Collection – Recruitment Procedures
Interviewers were trained to make multiple call-backs for various reasons including
inconvenient time, a message was left, or the call was unanswered after 10 rings. Those
congregations requiring call-back were called on different days and at different times during the
day. The interviewers were instructed to use their judgment in regard to the number of voice
messages left. Usually 1 message was considered sufficient, but further calls and messages were
warranted in case of a different “follow-up” interviewer or when trying to reach a specific
person. We avoided calls to congregations close to and during major holidays based on a
congregation’s religion. We also followed up once after a refusal. We tried calling the second
time on a different day/time of day to increase the probability of speaking with a different person
or catching somebody at a better time.
We did not conduct in-person follow-up. However, we sent a follow-up postcard and we
located email addresses for some congregations via the internet and personal contacts in the
community and contacted those congregations via email. The follow-up resulted in 28 additional
census completions.
D. Combined Theology-Polity Variable
Using ordered logistic regression analyses, we contrasted regressions of “having HIV
program[s]” on theology and polity as separate variables (an additive model) and on theology
and polity combined into a typology (an interaction model). The interaction-based typology
showed a marked, statistically significant improvement over the additive model. Thus, we used
a combined theology-polity (interaction) variable.
E. Scaled vs. Raw HIV Programming Data
The scaled data “correct” the raw data based on the census items by differentiating between
single and multiple-type program offerings (compare Table 2 with the table below). For
example, based on the HIV programming scale, 12% of Black Protestant congregations offered
education/prevention only, 9% offered education/prevention and counseling, and 15% offered all
3 types of programs. In contrast, in raw data, 33% of Black Protestant congregations offered
education/prevention, 18% counseling, and 15% testing (summing to 36% offering any
programming).
F. Description of the Black Protestant Group
There were 33 congregations in the Black Protestant category (7% of all congregations); 31
were congregational and 2 were episcopal in terms of polity. The majority (64%; N=21) were
affiliated with a denomination/convention: 14 Baptist (including National, United, American,
Southern, and Ohio conventions), 3 Church of God, 2 African Methodist Episcopal, 1
Pentacostal, and 1 Non-denominational (affiliated with Bible Way Church); 36% (N=12) were
not affiliated with a denomination/convention. In terms of theological orientation, 39% of the
Black Protestant congregations were “right in the middle”; 24% were “more on the conservative
side”; 18% were “more on the liberal side”; 9% were “clearly liberal”; and, 6% were “clearly
conservative.” In terms of religious identity/culture, 33% claimed no specific religious
culture/identity, 18% were Evangelical, 15% mainline, and 9.1% each Liberal and Charismatic;
the remaining were spread through other categories. The city-suburb split was 70%-30%. All
but 2 (94%) worshiped in a church/synagogue/temple vs. some other building.
Most (64%) of the Black Protestant congregations offered no HIV programming; 15%
offered education, counseling, and testing programs; 12% offered education programs only; and
9% offered education and counseling programs. Subgroup analysis was limited due to small
numbers. Generally, more congregations that were affiliated with a denomination/convention
offered HIV programs/services versus congregations that were not affiliated with a
denomination/convention (43% vs. 25%). Among the 14 Baptist congregations, 9 offered no
programs, 3 offered education, counseling, and testing programs, 1 offered education programs
only, and 1 offered education and counseling programs. There was not much difference between
congregations that were “more on the conservative side” and congregations that were “more on
the liberal side” – half of each offered no HIV programs/services; by comparison, 60% of
congregations that were “right in the middle” offered no HIV programs/services. In terms of
religious culture/identity, none of the 6 Evangelical congregations offered HIV
programs/services whereas 5 (45%) of those with no specific culture/identity offered some type
of HIV programs/services. Also, more Black Protestant congregations located in the central city
vs. a suburb (39% vs. 30%) offered HIV programming.
The sociodemographic and organizational characteristics of the Black Protestant category
vis-à-vis the other theology-polity groups are shown in the table below.
Comparison of theology-polity groups by selected characteristics
Central city location (%)
Years in existence (mean [median])
Changed worship site over time (%)
Size (regular attendance; mean [median])
Number of paid clergy & staff (mean [median])
Number of weekly worship sessions (mean [median])
Predominantly Black (%)
Predominantly more than high school education (%)
Predominantly ages 50+ (%)
Predominantly families with children (%)
Roman
Catholic/
Episcopal
Mainline
Protestant/
Episcopal
Mainline
Protestant/
Congregational
Conservative
Protestant/
Congregational
33
106 [104]
33
1750 [1950]
10 [7]
2 [2]
7
47
16
11
25
117 [120]
53
559 [343]
8 [6]
2 [1]
4
60
38
11
30
118 [123]
55
355 [259]
6 [6]
2 [3]
3
69
44
6
13
63 [51]
71
426 [265]
6 [4]
2 [2]
2
38
16
15
Black
Other Episcopal
Protestant/
& Congregational
Episcopal &
Congregational
70
66 [62]
79
602 [378]
10 [8]
2 [2]
85
30
3
9
9
85 [54]
82
949 [627]
6 [3]
2 [2]
9
91
27
18