Claims

Dosage effects and replicated results across methods support attributing observed outcomes to the City Connects intervention

Claim · All claims
Evidence · 1 study · causal r2 · q2
Currency · newest study 2015 · not yet checked against its sources · not reviewed by a person

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q2 i? The authors report dosage effects, successful addressing of selection bias via propensity weights, and replication of positive effects across evaluative studies as evidence consistent with a causal interpretation. → Walsh et al. 2015

Evidence

Walsh et al. 2015

Mary Walsh, Anastasia Raczek, Erin Sibley, Terrence Lee-St. John, Chen An, Bercem Akbayin, Eric Dearing, Claire Foley. (2015). City Connects: Building an Argument for Effects on Student Achievement with a Quasi-Experimental Design. SREE Spring 2015 Conference. https://eric.ed.gov/?id=ED562168

q2 · i? · causal · r2

This is the authors' logic-building argument in the Conclusions section, triangulating across the three quasi-experimental studies. The authors state that "more time in the program is associated with more improvement in outcomes" and that propensity-weighted groups are comparable. No effect size is printed for the dosage pattern.

"For example, we see dosage effects: more time in the program is associated with more improvement in outcomes. We see evidence that we have successfully addressed selection bias: after applying propensity weights to take pre-intervention differences into account, City Connects and comparison students are comparable."

Discussion

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