Gender differences in first choice match outcomes. by Lucy Hui (17538542)

Subjects:

Basic characteristics of the study participants by gender. by Subeen Kim (11714313)

Subjects:

Gender-disaggregated descriptive statistics for demographics, resources, and market factors. by Nancy Ndung’u (21601567)

Subjects:

Gendered descriptive statistics for socioeconomic capital, insect knowledge, and perception. by Nancy Ndung’u (21601567)

Subjects:

Selection model estimates for gender-specific determinants of participation in cricket farming. by Nancy Ndung’u (21601567)

Subjects:

Multinomial regression estimates of demographic, resource, and perception factors influencing household food security by gender of decision. by Nancy Ndung’u (21601567)

Subjects:

Brain regions with significantly decreased activations for the Raven task are shown in blue. by Morteza Fattahi (15892028)

Average proportion of first choice female applicants stratified by specialty category. by Lucy Hui (17538542)

Subjects:

Total number of applications to each discipline grouped by (a) clinical disciplines, (b) diagnostic disciplines, and (c) surgical disciplines. by Lucy Hui (17538542)

Subjects:

Number of applicants matched to each discipline grouped by (a) clinical disciplines, (b) diagnostic disciplines, and (c) surgical disciplines. by Lucy Hui (17538542)

Subjects:

Mean scores, standard deviations, and significance on key measures and subscales by gender group. by Silas Manning (22693338)

Alcohol-related monthly crude rates between 2018 and 2024, stratified by gender, age and cause of death. by Tony Wong (779773)

Subjects:

Percent change in yearly crude rates (between 2019 and 2021 and between 2019 and 2024) by gender and state. by Tony Wong (779773)

Subjects:

Alcohol-related monthly crude rates for ages 15 and older between 2018 and 2024, stratified by gender and race. by Tony Wong (779773)

Subjects:

Lecturers by gender. by Ignacio García-Espona (21395335)

“…Concerning gender, a clear imbalance in favour of men persists among lecturers. …”

Posters by gender. by Ignacio García-Espona (21395335)

“…Concerning gender, a clear imbalance in favour of men persists among lecturers. …”

R code for data analysis. by Mi Zhou (9884)

Subjects:

Description of demographics and PA results. by Mi Zhou (9884)

Subjects:

Odds ratios and 95% confidence intervals of micronutrient intakes below the estimated average requirement (EAR) in men according to frailty groups. by Subeen Kim (11714313)

Subjects:

Least-squares means (95% confidence intervals) of daily nutrient intake of study participants in men according to frailty groups. by Subeen Kim (11714313)

Subjects: