Head Start at Ages 3 and 4 Versus Head Start Followed by State Pre-K

The Effects of Tulsa's Pre‐K Program on Middle School Student Performance

“…The presence of a strong Head Start program in Tulsa probably helped TPS, by reducing the number of students to be served and by helping some three‐year‐olds to strengthen their skills before enrolling in TPS as four‐year‐olds (Gormley, Phillips, & Gayer, ; Jenkins et al., ). On the other hand, the Tulsa Head Start program also competed with TPS in the market for highly qualified pre‐K teachers.…”

“…As a fourth set of robustness checks, we employed alternative propensity score matching methods, including nearest neighbor matching and regression‐adjusted inverse‐probability weighting (Guo & Fraser, ) with the STATA commands teffects pscore and teffects ipwra . These commands cannot be used with the multiply imputed data so we used a missing‐indicator regression approach, as in a prior study with this sample (Jenkins et al., ). For both techniques, we rejected participants who were not within the range of common support, which resulted in dropping four participants.…”

Classroom Age Composition and the School Readiness of 3- and 4-Year-Olds in the Head Start Program

“…After children were matched, we examined the quality of the matches in several ways. First, we regressed each covariate on the indicator variable that distinguishes cases above the threshold from the comparison cases using the propensity score weight (see also, Jenkins et al, 2015), which allowed us to examine the propensity score adjusted means across groups. We also checked the standardized mean differences for all of our covariates across each comparison group, using the |.10| benchmark for assessing balance and the joint significance of overall balance using a Hotelling test.…”

“…The omission of peer effects from past evaluations of Head Start has left a critical gap in knowledge. In fact, classroom age composition may be one of the main reasons why the Head Start program has been documented as being less effective for older children as compared with younger children (Jenkins, Farkas, Duncan, Burchinal, & Vandell, 2015; Puma et al, 2010), although this possibility has yet to be tested.…”

Connecting College Students to Alternative Sources of Support: The Single Stop Community College Initiative and Postsecondary Outcomes

“…We assessed the baseline equivalence of key observable characteristics across the treatment and comparison groups to test this assumption, comparing the means of the two groups of students after applying the CEM weights to ensure that differences on all baseline covariates were no greater than 0.25 standard deviations (Ho et al, 2007). We also conducted statistical tests of baseline equivalence by regressing each covariate on the treatment variable using the CEM weights, following the recent empirical work by Jenkins et al (2016).…”