Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 1 |
| Since 2017 (last 10 years) | 1 |
| Since 2007 (last 20 years) | 3 |
Descriptor
Author
| Adam Sales | 1 |
| Charlotte Z. Mann | 1 |
| Green, T. | 1 |
| Holley, D. | 1 |
| Jaylin Lowe | 1 |
| Jiaying Wang | 1 |
| Johann A. Gagnon-Bartsch | 1 |
| Kadhi, T. | 1 |
| Krishna, K. | 1 |
| Ogolla, C. | 1 |
| Rene, E. | 1 |
| More ▼ | |
Publication Type
| Reports - Research | 2 |
| Speeches/Meeting Papers | 2 |
| Reports - Evaluative | 1 |
Education Level
| Elementary Secondary Education | 1 |
| Grade 8 | 1 |
| High Schools | 1 |
| Higher Education | 1 |
| Junior High Schools | 1 |
| Middle Schools | 1 |
| Secondary Education | 1 |
Audience
Location
| Texas | 3 |
Laws, Policies, & Programs
| No Child Left Behind Act 2001 | 1 |
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkJaylin Lowe; Charlotte Z. Mann; Jiaying Wang; Adam Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…
Descriptors: Randomized Controlled Trials, Middle School Mathematics, Middle School Students, Middle Schools
Download full textKadhi, T.; Rudley, D.; Holley, D.; Krishna, K.; Ogolla, C.; Rene, E.; Green, T. – Online Submission, 2010
The following report of descriptive statistics addresses the attendance of the 2012 class and the average Actual and Predicted 1L Grade Point Averages (GPAs). Correlational and Inferential statistics are also run on the variables of Attendance (Y/N), Attendance Number of Times, Actual GPA, and Predictive GPA (Predictive GPA is defined as the Index…
Descriptors: Grade Point Average, Law Schools, Statistical Analysis, Databases
Roane, Warren – Online Submission, 2010
The Texas Projection Measure (TPM) has grown out of the state's need to meet the requirements of No Child Left Behind (NCLB). An examination of the state's method of predicting 8th grade mathematics scores reveals that several factors have been ignored in the process of developing the model, including assumptions in its underlying statistical…
Descriptors: Federal Legislation, Statistical Analysis, Grade 8, Predictive Measurement
