# Journal of College & University Student Housing Volume 48, No. 2 - 18

```How Interactions Contribute to Thriving
Out of the 24 regression equations tested from the initial model, we removed eight
that were non-significant for the final model. Sriram (2017) notes that a moderate
effect size without statistical significance means there is a real difference found in the
sample, but we cannot (with adequate confidence) infer that about a larger population.
Although these changes altered pathways from the proposed model, it was important
to take effect sizes into account along with p-values.
We then analyzed modification indices to explore additional variations affecting
goodness-of-fit. As researchers, it was important to not allow computer software to
dictate how the theory under study was conceptualized. With that understanding,
we implemented two theoretically supported changes: adding regression equations
between thriving factors (which also allowed for an observation of mediating relationships)
and adding a regression equation from academic interactions with staff to
diverse citizenship. While improving model fit, these relationships were also justified
based on the review of literature (Astin et al., 2011; Cole & Griffin, 2013; Kim & Sax,
2014). After these adjustments, the final model was improved and remained parsimonious,
demonstrated through satisfactory fit indices [χ2 = 1706.689 (df = 1190,
p < .001), CFI = .933, RMSEA = .046]. The final structural model is represented in
Figure 1 below. Squared multiple correlations (R2), which correspond to the percentage
of variance in the endogenous/outcome variables explained by the exogenous/
predictor variables, are summarized in Table 2.
Direct effects, the equivalent of path coefficients (which indicate the effects
of an assumed cause variable on an assumed effect variable) are offered in Table 3
(see page 20) as standardized beta weights. For effect size thresholds, recommendations
for higher education research from Mayhew, Pascarella, et al. (2016) were used
as follows: .06 as small, .12 as medium, and .20 as large. The aim of this study was to
validate a model that identified how certain interaction variables contribute to college
student thriving for sophomore, junior, and senior LLC students. The creation of this
predictive structural equation model established the utility of using various student
interactions with different constituents to predict factors of success for such students.
LIMITATIONS
There are certain limitations that should be considered when interpreting the results
of this study. The first concerns the sample (N = 206). Although the dataset comprised
a range of students from multiple institutions and LLCs, it is not representative
of all sophomore, junior, and senior students enrolled in four-year universities.
Choosing LLC students was intentional due to the frequency of interaction these environments
generate. However, non-LLC students likewise have interactions across
campus and may experience relationships in different ways. Further, different LLC
structures on different types of campuses may promote interactions in distinct ways.
Future research should consider using typologies such as those from Inkelas et al.
(2008) as a framework for parceling out how LLC student interactions may contribute
to student success based on community structure.
18 The Journal of College and University Student Housing
```

# Journal of College & University Student Housing Volume 48, No. 2

## Table of Contents for the Digital Edition of Journal of College & University Student Housing Volume 48, No. 2

Journal of College & University Student Housing Volume 48, No. 2 - intro
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Journal of College & University Student Housing Volume 48, No. 2 - Cover3
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