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

BMI groups by SES. by Krystal Hunter (6820052)

“…This is a case control study using the <a href="http://www.cdc.gov/nchs/births.htm" target="_blank">Natality</a> Data of the <a href="http://www.cdc.gov/nchs/nvss.htm" target="_blank">National Vital Statistics System</a> from the years 2020–2022. BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”

BMISES_Data_Part2. by Krystal Hunter (6820052)

“…This is a case control study using the <a href="http://www.cdc.gov/nchs/births.htm" target="_blank">Natality</a> Data of the <a href="http://www.cdc.gov/nchs/nvss.htm" target="_blank">National Vital Statistics System</a> from the years 2020–2022. BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”

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

“…This is a case control study using the <a href="http://www.cdc.gov/nchs/births.htm" target="_blank">Natality</a> Data of the <a href="http://www.cdc.gov/nchs/nvss.htm" target="_blank">National Vital Statistics System</a> from the years 2020–2022. BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”

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

“…This is a case control study using the <a href="http://www.cdc.gov/nchs/births.htm" target="_blank">Natality</a> Data of the <a href="http://www.cdc.gov/nchs/nvss.htm" target="_blank">National Vital Statistics System</a> from the years 2020–2022. BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”

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

“…This is a case control study using the <a href="http://www.cdc.gov/nchs/births.htm" target="_blank">Natality</a> Data of the <a href="http://www.cdc.gov/nchs/nvss.htm" target="_blank">National Vital Statistics System</a> from the years 2020–2022. BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”

BMISES_Data_Part1. by Krystal Hunter (6820052)

“…This is a case control study using the <a href="http://www.cdc.gov/nchs/births.htm" target="_blank">Natality</a> Data of the <a href="http://www.cdc.gov/nchs/nvss.htm" target="_blank">National Vital Statistics System</a> from the years 2020–2022. BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”

Baseline characteristics of HSES/LSES population. by Krystal Hunter (6820052)

“…This is a case control study using the <a href="http://www.cdc.gov/nchs/births.htm" target="_blank">Natality</a> Data of the <a href="http://www.cdc.gov/nchs/nvss.htm" target="_blank">National Vital Statistics System</a> from the years 2020–2022. BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”

Baseline characteristics of overall population. by Krystal Hunter (6820052)

“…This is a case control study using the <a href="http://www.cdc.gov/nchs/births.htm" target="_blank">Natality</a> Data of the <a href="http://www.cdc.gov/nchs/nvss.htm" target="_blank">National Vital Statistics System</a> from the years 2020–2022. BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”

Diagram of study population. by Krystal Hunter (6820052)

“…This is a case control study using the <a href="http://www.cdc.gov/nchs/births.htm" target="_blank">Natality</a> Data of the <a href="http://www.cdc.gov/nchs/nvss.htm" target="_blank">National Vital Statistics System</a> from the years 2020–2022. BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”

Results of the generalized linear mixed model (GLMM) for correct responses in the speech recognition task. by Elena Bolt (20396190)

Results of linear mixed models (LMMs) on linguistic timescale tracking for the phrase, word, syllable, and phoneme rates. by Elena Bolt (20396190)

Univariate linear regression analysis of scales. by Xiangyu Wang (341093)

Results of the linear models for the amplitudes (in <i>μ</i>V) of the components P1, N1, P2, and N400. by Elena Bolt (20396190)

A Comparison of Pediatric Prehospital Opioid Encounters and Social Vulnerability by Stephen Sandelich (19991783)

“…The analysis demonstrated that as socioeconomic status (SES) improves, the likelihood of opioid-related activations increases significantly supported by a significant negative linear trend (Estimate = −0.2971, SE = 0.1172, z = −2.54, <i>p</i> = 0.0112. …”

Flowchart of participants in this study. by Yubo Teng (21246745)

“…Hypertension was found to be a significant factor influencing the relationship between UACR and cognitive impairment (<i>P</i> for interaction < 0.05).…”

Association between FF Proximity and BMI by sex. by Kimberly Yuin Y’ng Wong (22766265)

“…The overall association between FF proximity and BMI was not significant but modified by sex (p-_{heterogeneity} <0.001). …”

Recruitment flow diagram of the current study. by Somayeh Momenyan (10111603)

“…Phase 1 EQ-VAS decreases were associated with female sex, lower somatic symptom, fewer comorbidities, lack of expectation for a fast recovery, higher ISS, higher injury pain, neck, spine/back or lower extremity injuries. …”

Factors influencing cognitive response. by Yang Li (7082)

“…Finally, two Generalized Linear Mixed Models were developed to examine factors affecting driving stability, focusing on speed and steering control. …”

Factors associated with malaria infection. by Job Oyweri (22041452)

“…Logistic regression was used to identify factors influencing net ownership and malaria prevalence, while a generalized linear model assessed factors affecting net usage. …”