Targeted Outreach - Governor's Office of Crime Control & Prevention ...

68 Targeted Outreach
• log (p/[1-P]) = a + b2X + b3T+ b4P + e1
Where: p = the probability that Y2 = 1
1-p = the probability that Y2= 0
a,,bi,T, P and ei are defined as in equation (1),
but on a logit scale.
Only those youth who, at baseline, had reported never having
used illegal drugs were included in the logistic regression
analyses estimating the effect of GPTTO on initiations
of drug use. Similarly, only those youth who had at baseline
reported never having used alcohol were included in
the analyses estimating impact on initiation of alcohol use.
Therefore, the baseline assessment of these outcome variables
was not included in these models.
As in the OLS models, explanatory variables controlling
for pre-existing differences among the youth are included
in the logit included models, and subgroup-treatment
interaction variables are included in models estimating
impacts for gender and age subgroups.
The key finding of the analysis is whether GPTTO or
GITTO has an effect on various outcome measures. In the
discussion of the results, we indicate whether an impact
estimate is statistically different from zero by labeling statistically
non-zero estimates as “significant.” In this report,
the term is reserved for estimates that were not equal to
zero at a 0.10 or greater level of significance using a twotailed
t-test. These “significant” impacts are indicated in
the tables and text with asterisks (*).
In summary, a variety of analytic strategies were used to
evaluate the effect of participation in GPTTO and GITTO.
The fundamental approaches used a dummy variable
(indicating treatment or control group status) or a continuous
participation variable (indicating level of frequency
of involvement in the Club/Project) in an OLS regression.
Other analyses (e.g., logit analysis) were used where the
assumption of the OLS model were likely to be violated,
such as when the outcome variable was dichotomous.