Results 51 to 60 of about 5,788,827 (317)
Building a Multiple Linear Regression Model With LEGO Brick Data
We present an innovative activity that uses data about LEGO sets to help students self-discover multiple linear regressions. Students are guided to predict the price of a LEGO set posted on Amazon.com (Amazon price) using LEGO characteristics such as the
Anna D. Peterson, Laura Ziegler
doaj +1 more source
A hybrid of multiple linear regression clustering model with support vector machine for colorectal cancer tumor size prediction [PDF]
This study proposed the new hybrid model of Multiple Linear Regression Clustering (MLRC) combined with Support Vector Machine (SVM) to predict tumor size of colorectal cancer (CRC).
Ismail, Shuhaida +3 more
core +1 more source
ABSTRACT Treatment‐associated hepatotoxicity (TAH) is a common complication of pediatric acute lymphoblastic leukemia (ALL) treatment, but genetic risk factors remain poorly understood. We evaluated the SOD2 rs4880 variant in 544 children with ALL at Texas Children's Hospital. After adjusting for demographic and clinical covariates, the rs4880 C allele
Emily J. Mason +14 more
wiley +1 more source
The Linear Regression Model [PDF]
Constantin Anghelache +4 more
semanticscholar +3 more sources
Admissibility of the usual confidence interval in linear regression
Consider a linear regression model with independent and identically normally distributed random errors. Suppose that the parameter of interest is a specified linear combination of the regression parameters. We prove that the usual confidence interval for
Giri, Khageswor +2 more
core +1 more source
ABSTRACT Background Osteosarcoma (OS) and Ewing sarcoma (EWS) are the most common primary bone cancers in children, but acute thrombosis is poorly characterized in this population. Our study evaluated the rates of venous thromboembolism (VTE) and associated risk factors in pediatric patients with bone sarcomas treated over a 10‐year period encompassing
Sarah Kappa +8 more
wiley +1 more source
OPLS statistical model versus linear regression to assess sonographic predictors of stroke prognosis
Kianoush Fathi Vajargah,1 Homayoun Sadeghi-Bazargani,2,3 Robab Mehdizadeh-Esfanjani,4 Daryoush Savadi-Oskouei,4 Mehdi Farhoudi41Department of Statistics, Islamic Azad University, Tehran, North Branch, 2Neuroscience Research Center, Department of ...
Fathi Vajargah K +4 more
doaj
A learning system-based soft multiple linear regression model
Machine learning applied to regression models offers powerful mathematical tools for predicting responses based on one or more predictor variables.
Gholamreza Hesamian +3 more
doaj +1 more source
INFERENCE AFTER MODEL AVERAGING IN LINEAR REGRESSION MODELS
This article considers the problem of inference for nested least squares averaging estimators. We study the asymptotic behavior of the Mallows model averaging estimator (MMA; Hansen, 2007) and the jackknife model averaging estimator (JMA; Hansen and ...
Xinyu Zhang, Chu-An Liu
semanticscholar +1 more source
ABSTRACT Background This study investigated how neighborhood‐level social determinants of health (SDOH), including redlining and neurological risk, interact to influence cognitive outcomes in children treated for brain tumors (CTBT). Methods A retrospective chart review of 161 CTBT aged 5–17 was conducted.
Alannah R. Srsich +5 more
wiley +1 more source

