Excluded studies with reasons for exclusion. by Si He (3236646)

Subjects:

Subgroup Analysis of the Occurrence of the Primary Endpoint and Its Components. by Karl Ingard (22582091)

Subjects:

Flow diagram of the studies included in the meta-analysis. by Si He (3236646)

Subjects:

Mean muscle activation patterns across the gait cycle during walking with mediolateral (ML) forces for <i>A)</i> able-bodied individuals and <i>B)</i> individuals after stroke duri... by Sanne Ettema (18786312)

Comparison of TNF- by Mahshid Vafajoo (21144147)

Each group’s performance on behavioral tests. by Wenbin Wu (292223)

Improvement effect of lactoferrin and Coenzyme Q10 on body composition of mice with sarcopenia. by Wenbin Wu (292223)

Univariate analyses. by Zachary E. M. Giovannini-Green (22008277)

“…Multiple linear regression with Generalized Estimating Equations (GEE) modelling was used to identify factors associated with mean monthly ED visits. Multivariate analysis showed the mean monthly ED visits increased significantly during the first year of COVID-19 than before the pandemic (Mean = 0.30 vs Mean = 0.21, p = 0.01). …”

Overview of individuals in the study. by Zachary E. M. Giovannini-Green (22008277)

“…Multiple linear regression with Generalized Estimating Equations (GEE) modelling was used to identify factors associated with mean monthly ED visits. Multivariate analysis showed the mean monthly ED visits increased significantly during the first year of COVID-19 than before the pandemic (Mean = 0.30 vs Mean = 0.21, p = 0.01). …”

Multivariate analyses. by Zachary E. M. Giovannini-Green (22008277)

“…Multiple linear regression with Generalized Estimating Equations (GEE) modelling was used to identify factors associated with mean monthly ED visits. Multivariate analysis showed the mean monthly ED visits increased significantly during the first year of COVID-19 than before the pandemic (Mean = 0.30 vs Mean = 0.21, p = 0.01). …”

Population dynamics reflect intention-action binding. by Jean-Paul Noel (3072192)

Prisma flow diagram of study selection. by Hattapark Dejakaisaya (22238613)

“…Additionally, watching ≥6 hours of television per day was associated with a significant decrease in cognitive score (standardized beta coefficient = −0.09; 95% CI: −0.17, −0.003; I² = 71.8%; seven studies). …”

Surgical changes through ISIW implantation. by Sayaka Kimura-Uchida (22793666)

“…Pre- and postoperative data are compared by Tukey’s HSD test and asterisks mean statistical significance (p < 0.05). IOP decreases significantly from 3 to 12 months after surgery whereas GMS decreases from one day to 12 months after surgery. …”

BMI groups by SES. by Krystal Hunter (6820052)

“…Our objective is to fill in the knowledge gap by evaluating the interaction of socio-economic status (SES) and BMI and its relationship to the rate of PTB. …”

BMISES_Data_Part2. by Krystal Hunter (6820052)

“…Our objective is to fill in the knowledge gap by evaluating the interaction of socio-economic status (SES) and BMI and its relationship to the rate of PTB. …”

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

“…Our objective is to fill in the knowledge gap by evaluating the interaction of socio-economic status (SES) and BMI and its relationship to the rate of PTB. …”

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

“…Our objective is to fill in the knowledge gap by evaluating the interaction of socio-economic status (SES) and BMI and its relationship to the rate of PTB. …”

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

“…Our objective is to fill in the knowledge gap by evaluating the interaction of socio-economic status (SES) and BMI and its relationship to the rate of PTB. …”

BMISES_Data_Part1. by Krystal Hunter (6820052)

“…Our objective is to fill in the knowledge gap by evaluating the interaction of socio-economic status (SES) and BMI and its relationship to the rate of PTB. …”

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

“…Our objective is to fill in the knowledge gap by evaluating the interaction of socio-economic status (SES) and BMI and its relationship to the rate of PTB. …”