Addressing the Gap in Oncologist Training by Skylar Gay (20696057)

Linear trends of the weekly total cost and cost components per capita for inpatients in the non-surgical group. by Chenxuan Zhu (22622476)

Linear mixed models. evolution of posttraumatric stress symptomatology scores according to socio-demographic and occupational variables, from baseline to 12 months. by Beatriz Arregui-Gallego (21553735)

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Based on our time series data(first from the left), the visualizations of linear residual predictions under different decimation rates (next three) show that as the decimation rate... by Hua Huo (1818133)

Questionnaire description. by Cristobal Padilla-Fortunatti (21376807)

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Linear relationship between sleep duration and cardiovascular disease (CVD) risk in type 2 diabetes patients. by Zhi Jin (3742471)

Multiple linear regression analysis of the RAAS system and glucose metabolism indexes in HT and NT patients. by Ningning Wang (560944)

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Cohesion characteristics and statistical significance analysis of different ingredients across IDDSI levels^b'*'. by Muxi Chen (9294270)

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Adhesion characteristics and statistical significance analysis of different ingredients across IDDSI levels^b'*'. by Muxi Chen (9294270)

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Hardness characteristics and statistical significance analysis of different ingredients across IDDSI levels^b'*'. by Muxi Chen (9294270)

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Factors associated with the hemoglobin level stratified by age group: Linear regression. by Alejandro Rojas Chaves (20614814)

Summary of structural dynamics of WT and mutant RhoGAPs-RhoA complexes. by Zen Kouchi (14898435)

Multiple Linear Regression of the Effects of Work Resources and Prior Traumatic Events on Stress Specific to COVID-19. by Rachel G. Baskin (22127334)

Classes of errors and gaps in BOLD metadata. by Frederik Stein (22146203)

“…ASAP was found to be superior to RESL due to RESL’s adherence to the concept of the DNA barcoding gap. Moreover, we found that taxonomic misassignments, inconsistencies in BIN formation, and missing metadata also contribute significantly to unreliable identifications. …”

BMI groups by SES. by Krystal Hunter (6820052)

“…We also found that the relationship between BMI and PTB was not linear but curvilinear, bridging the gap in the conclusions of other studies. …”

BMISES_Data_Part2. by Krystal Hunter (6820052)

“…We also found that the relationship between BMI and PTB was not linear but curvilinear, bridging the gap in the conclusions of other studies. …”

Logistic regression for LSES population. by Krystal Hunter (6820052)

“…We also found that the relationship between BMI and PTB was not linear but curvilinear, bridging the gap in the conclusions of other studies. …”

Logistic regression for HSES population. by Krystal Hunter (6820052)

“…We also found that the relationship between BMI and PTB was not linear but curvilinear, bridging the gap in the conclusions of other studies. …”

Logistic regression for overall population. by Krystal Hunter (6820052)

“…We also found that the relationship between BMI and PTB was not linear but curvilinear, bridging the gap in the conclusions of other studies. …”

BMISES_Data_Part1. by Krystal Hunter (6820052)

“…We also found that the relationship between BMI and PTB was not linear but curvilinear, bridging the gap in the conclusions of other studies. …”