1. 2012
Dillard Mid Year
Retention Monitoring
Report
Incorporating a Repeat Measurement
Approach
The predictors of retention are time sensitive; their effects differ by magnitude
over the course of first year matriculation.
wkirkland
Dillard University
3/9/2012

2. In 2011, the Office of Institutional Research, using the 2010 first-time freshmen cohort,
developed for the first time a Dillard specific regression model to identify variables that predict
first year to second year retention at the institution. The model yielded substantial information
about factors influencing student retention at Dillard. The original study produced the following
abstract:
Declining student retention has been the subject of serious discussion among
decision-makers at Dillard University during the past two years. The most common
explanation suggests the cause for the low rate centers around the issue of student
academic preparation, especially the academic profile of admitted first-time freshmen.
This study analyzes the impact of nine independent variables in predicting retention for the
entering freshmen cohort group of Fall 2010. Despite expectations that academic
preparation would be a predictor, little evidence is found that standardized test score
(ACT) and/or high school grade point average (HSGPA) have a positive influence on
retention. The opposite is true for ACT composite score; it is negatively related to
retention. HSGPA has no influence. The most potent predictor of retention is the amount
of unmet financial aid need. It is also negatively related to retention but in a positive way.
As the amount declines retention increases. The second best predictor is academic
performance, or first semester grade point average. Thus, the evidence shows that unmet
financial needs play an equal or greater role as academic performance in predicting
retention.
Now, for the first time the model is being applied not only to assess the 2011 cohort but
its retention from the first to second semester period. The purpose of this analysis is to provide
greater clarity to Dillard policymakers about the relationship between retention predictors and
the first year matriculation cycle.
Repeated Measurement Approach
What the original study did not address is how long after matriculation starts do the
effects of the predictors begin to influence retention? Since the release of the results of the
original study the office has embarked on developing a continuing process to monitor retention at
different stages of new freshmen matriculation. Instead of limiting analyses of cohort retention
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3. from first year to second year, the office is applying the model from the first semester to second
semester as well. By implementing a repeated measurement design approach it is hoped that the
office will be able to tease out the effect of each variable at different points in time and perhaps
better understand how quickly each one influences retention over the course of the first year
matriculation cycle. It may be that some variables play a greater role in influencing retention at
different points in time. The advantage of knowing this is that it may allow policymakers to
develop more complex strategies that take into account the timing of each variable’s effect as a
means of addressing retention issues.
2011 Cohort Analysis
The analysis provides evidence that the predictive power of the variables identified in the
original study appear to be time sensitive. While the original analysis found that unmet financial
aid need amount (beta weight -.368) and first semester GPA (beta weight .324) contributed
equally to predicting first to second year retention, results from the first to second semester
analysis for the Fall 2011 cohort show a much different pattern. The influence of unmet
financial aid amount (beta weight -.581) is three times greater than first semester GPA (beta
weight .173) in predicting retention during this period. Also, although first semester GPA is still
a predictor, its influence is a little more than half of what it was in predicting first to second year
retention. The influence of third predictor variable, ACT score, is similar in both magnitude and
direction during both periods (beta weight -.131 to -.176). However, it failed to reach statistical
significance during the early stage.
In essence, the nature of the relationship between the most potent predictors and retention
identified in the original analysis of the 2010 cohort group are sustained in the 2011 cohort
group. In addition, the direction of the relationships also remained the same, unmet financial aid
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4. amount and ACT score remain negatively related to retention, and first semester GPA is
positively related to retention.
Retroactive Analysis of 2010 Cohort
The results gleaned from the 2011 cohort analysis triggered an interest in retroactively
applying the model to the 2010 cohort group during the first to second semester period. The
findings support the notion that the influence of the predictor variables vary according to time.
Among the 2010 cohort the influence of unmet financial aid need amount (beta weight -.702) is
five times greater than first semester GPA (beta weight .119) during the early period. Yet they
contribute almost equally in predicting retention for the second year. This suggests that
academic performance is less likely to influence retention during the early period than it will at a
later point for this group.
The results also buttress the reliability of the model as it predicts that unmet financial aid
need amount is an extremely strong predictor during the early stages of matriculation for both
cohorts (beta weight -.702 and -.581). Based on these findings it is expected that the influence of
unmet need will probably wane for the 2011 cohort in the later part of matriculation while the
influence of first semester GPA will wax stronger. The analysis reveals one constant - that is -
the influence of ACT score appears not to be sensitive to time sequence. In both scenarios, ACT
score is negatively related to retention. In addition its influence seems to remain constant no
matter the period (beta weight -.131, -.150 and -.176).
After assessing these results a third stage analysis was performed on the 2010 cohort to
assess the effect of each variable during the period between the second semester of the first year
and the beginning of the first semester of the second year. The results show that first semester
GPA is much stronger during this period (beta weight .346) compared to (beta weight .119)
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5. during the earlier period. Additionally, the influence of unmet need (beta weight -.168) is four
times less (beta weight -.702) during this period than during the earlier period. The influence of
ACT score remains consistent no matter the period (beta weight -.176,) year to year, (beta weight
-.150) first to second semester, and (beta weight and -.160) second semester to second year. In
addition, both unmet financial aid need amount and ACT score failed to reach statistical
significance during this period.
In conclusion, these analyses have explicated different levels of influence at different
times for predictor variables in the model. During the first year, various factors effect retention
at different times during the matriculation cycle. That being said, attrition at Dillard is strongly
driven by unmet financial need during the early stage of freshmen matriculation and by academic
performance during the latter stage of the matriculation. This knowledge may aid policymaker
in developing intervention strategies that are time sensitive. Once such strategies have been
implemented the next logical step would be to develop a reliable intervention analysis
methodology to monitor the effects of those strategies.
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