Regression to Predict Absences on MAP Scores Student Absences and School Achievement Rakeyta Benjamin, MS Robert Bridger, Crystal Hill-Chapman, & Samuel Broughton Francis Marion University ABSTRACT One hundred elementary aged children’s data were used to determine if absences and demographic variables predict school achievement. Results indicated that absences significantly predicted MAP (Measures of Academic Progress) reading and math scores. No demographic variables predicted absences or school achievement. METHODS Participants The sample comprised 100 (50 females and 50 males) third through fifth graders derived from a larger data set. Data for the 2013-2014 school year were obtained from the school district’s network system. All participants attend a small elementary school in Marion County School District. All participants receive free and reduced lunch due to the school being a Title I school. Also, the poverty level in Marion County through 2009-2013 was 27.4% (U.S. Census Bureau, 2013). Procedure The data for this study were collected from a larger data set. Researchers collected data from students at a rural school. Student names were removed to protect privacy. Additionally, researchers chose to use MAP spring 2013 reading and math scores to measure achievement. Unexcused and excused absences during the 2013 school year for each participant were counted as well. Researchers also gathered demographic information which included: gender, race, and free lunch status. Measures Measures of Academic Progress. We defined student achievement as performance on a statewide MAP (Measures of Academic Progress) standardized test. Reading and math scores from spring 2013 were used (Northwest Evaluation Association, 2011). Table 1 Regression to Predict Absences on MAP Scores   Absences F R²Adj β p r 3.83 .054 MAP Reading -.043 .02 -.232 MAP Math -.082 .01 -.255 Note. MAP = Measures of Academic Progress PURPOSE AND HYPOTHESIS The aim of this study is to examine whether absences significantly predict school achievement. Additionally, the researchers hypothesize that certain demographic variables will predict absences and school achievement. RESULTS A multiple regression analysis was used to test if absences significantly predicted MAP (Measures of Academic Progress) scores. The results of the regression indicated that absences significantly predicted MAP reading and math scores (see Table 1). Demographic variables such as gender, free lunch status, and race did not predict absences or school achievement. BACKGROUND “At least half of life is just showing up” is a familiar quote spoken by the actor Woody Allen. When students miss days of school, many teachers may share Woody Allen’s opinion. Educators may share this opinion because it has been shown that attendance contributes to academic success (Westerman, Perez-Batres, Coffey & Pouder, 2011). Additionally, educators are concerned because absences may lead to poor grades and further absenteeism (Parke & Kanyongo, 2012). Student absences are more prevalent among children living in low income areas. However, students living in low income areas benefit the most from attending classes every school day (Balfanz & Byrnes, 2012). Balfanz and Byrnes (2012) reported that students who live in high poverty neighborhoods and attend school every have more positive outcomes, even without any additional interventions or strategies. Therefore, developing strategies and incentives to assist students who live in high poverty areas to attend school every day may improve the American education system, and lead to higher achievement, high school graduation rates, and college attainment (Balfanz & Byrnes, 2012). The reasons behind student absences are complex, but being knowledgeable of risk and protective factors will assist educators with developing appropriate strategies to get students who live in poverty stricken areas to attend school every day. CONCLUSION The aim of this study was to examine if absences predict achievement. We supported our hypothesis that absences predicted MAP scores. However, we did not find demographic variables to predict achievement or absences. Being knowledgeable and aware of risk and protective factors associated with student absences may assist with improving students’ achievement. Students who have lower rates of absences are more likely to obtain higher levels of achievement, especially children from low income families. These findings suggest that attendance is important for academic achievement. Being proactive about getting students to attend classes may foster resilience, and counteract risk factors. Therefore, acting as a protective factor for children who are at risk for having higher rates of absences during the school year, especially students in poverty stricken areas. Future studies, may consider obtaining a larger sample size and looking at a sample that includes participants from different geographic areas. Additionally, investing the effectiveness of interventions that reduce absences is needed. Overall, our results were significant and that warrants more research.