5.2.2 Incoming Literacy & Numeracy

“I noticed three main differences between Bridge [PSL public schools] and traditional public schools. First, the traditional schools did not have sufficient desks for students, but Bridge PSL schools had. Second, traditional schools did not have full instructional staff on campus, but Bridge PSL schools had. Third, Bridge PSL students had textbooks and could read them.”

~ Daowomah Bono, Graduate Student in Education Administration, University of Liberia

9. Limitations

One of our main concerns is attrition; 29% of students in our study sample were not in school during endline assessments, making it impossible to collect data on their outcomes. Unfortunately, tracking students outside of their baseline school is cost-prohibitive for the scope of this study, so we were therefore constrained by the schedules of comparison schools and whether students happened to be absent during assessment days. Where students moved grade levels, however, we did our best to locate them within their baseline school, and their results are analyzed per their starting grade level.

9.1 Attrition

Sample attrition rates at midlines and endlines by Bridge PSL public and traditional public schools can be seen in Table 31. The overall average sample attrition rate was slightly lower for Bridge PSL public schools than traditional public schools at midlines, but higher at endlines.

Table 31. Sample Attrition at Midlines vs. Endlines

Sample attrition is not the same as attrition from schools. Reasons for attrition from the sample can be seen in Table 32. As of the date of this report, endline analysis shows that around 16% of students were not assessed because they have withdrawn. While about 4% of students have moved, 12% have withdrawn for other reasons65. About 8% of the students were not assessed because they were absent. Note that a larger percentage of Bridge PSL public school students were absent compared to traditional public school students. Given that the majority of assessments at Bridge PSL public schools was conducted in the afternoon during the extended day periods, there is a possible bias toward absenteeism at Bridge PSL public schools.

65 The “other” withdrawal reasons reported for Bridge PSL public schools included: farming/selling (9 students), transferred to a traditional public school (7 students), pregnancy (4 student), the length of the PSL school day (3 students), lack of feeding (2 students), and being demoted (1 student). The “other” withdrawal reasons reported for traditional public schools included: farming/selling (21 students), pregnancy (3 students), and playing soccer (1 student).

Table 32. Endline Status of Students from Baseline Sample

Sample attrition can greatly impact results if the reasons for the attrition are different across school types. To ensure our estimates of the Bridge effect are not biased, we test for differential attrition below. An explanation of why sample attrition, and particularly differential attrition, is a concern can be found in Appendix A11. Why Sample Attrition is a Concern.

9.2 Differential Attrition

Attrition only biases our results if it differentially impacts students who received the treatment. For example, let’s assume that students who performed poorly at baselines had less gains than students who performed well. If students who were performing poorly left School A but those types of students stayed at School B, it would appear that School A had differential gains when in actuality the final sample of students is not comparable.

In the following two sections, we explore the possibility of differential attrition in our sample. First, we look at differential attrition by baseline characteristics, then we review differential attrition by mid-year growth differences.

9.2.1 Differential Attrition by Baseline Characteristics

Using the baseline sample, we created an indicator on whether the student attrited from the sample by endlines. We then used a regression framework to examine whether particular types of students attending Bridge PSL public schools were more likely to attrite than their counterparts attending traditional public schools. The key factors we worry about are incoming levels of literacy and numeracy (the EGRA and EGMA subtask scores). For the ease of interpretation, we created a composite variable for EGRA and EGMA subtasks.66

We ran three different sets of specifications in order to balance between including all baseline information and losing statistical power due to too many interaction effects. On the whole, we do not see systematic differences in attrition rates by school type, but do see some differences by student type.

While students’ EGRA scores do not correlate with attrition, students with higher EGMA scores at baselines were less likely to attrite. Older students or those who did not attend school the previous year were also more likely to attrite. Again, this is the case for both Bridge PSL public schools and traditional public schools.

66 Composite EGRA/EGMA scores were created by taking the standardized baseline score for each subtask and averaging this score across subtasks. We used a unit weight, which suggests each outcome is equally important. For a discussion on composites, see Schochet (2008).