Results of multiple regression analyses predicting level of participation for males (number of male participants) by economic classification (EC) and GDP (95% confidence intervals for b in parentheses).

Multiple regression analyses predicting SOS, BUA and SI for adolescent males.

Mohamed S. Zulfarina (5628941)
Razinah Sharif (5628944)
Syed-Badrul Syarifah-Noratiqah (5628947)
Ahmad M. Sharkawi (5628950)
Zaris-SM Aqilah-SM (5628953)
Sabarul-Afian Mokhtar (5628956)
Shuid A. Nazrun (5628959)
Isa Naina-Mohamed (5628962)

August 2018

Multiple regression analyses predicting SOS, BUA and SI for adolescent males.</p

Meta-regression of (A) percentage male, (B) mean age, and (C) interventions for overall survival.

Chenxi Zhong (388871)
Hongcheng Liu (388872)
Liyan Jiang (388873)
Wei Zhang (405)
Feng Yao (44334)

March 2013

Meta-regression of (A) percentage male, (B) mean age, and (C) interventions for overall survival....

Stratified multivariate analyses of recession indicators (during and after) and mental health indicators for males.

Rada K. Dagher (738599)
Jie Chen (5892)
Stephen B. Thomas (738600)

May 2015

* p ≤ 0.05;** p ≤ 0.01;*** p ≤ 0.001Stratified multivariate analyses of rece...

Results of multiple regression analyses predicting level of participation for females (number of female participants) by economic classification (EC) and GDP (95% confidence intervals for b in parentheses).

Leslie Swartz (162980)
Jason Bantjes (3394580)
Divan Rall (3394583)
Suzanne Ferreira (3394586)
Cheri Blauwet (3394577)
Wayne Derman (3394589)

December 2016

Results of multiple regression analyses predicting level of participation for females (number of ...

Results of multiple regression analyses predicting level of participation for females (number of medals won by female participants) by economic classification (EC) and GDP (95% confidence intervals for b in parentheses).

Leslie Swartz (162980)
Jason Bantjes (3394580)
Divan Rall (3394583)
Suzanne Ferreira (3394586)
Cheri Blauwet (3394577)
Wayne Derman (3394589)

December 2016

Results of multiple regression analyses predicting level of participation for females (number of ...

Logistic regression analysis results for the Male population.

Thomas N. O. Achia (694800)

February 2015

* p<0.05** p<0.01*** p<0.0.Logistic regression analysis results for the Male...

Regression Results: Additive Model with Sex Specific Effects.

Coren L. Apicella (91036)
David Cesarini (123128)
Magnus Johannesson (123135)
Christopher T. Dawes (281512)
Paul Lichtenstein (47559)
Björn Wallace (364028)
Jonathan Beauchamp (364031)
Lars Westberg (364033)

February 2013

Notes: This table reports regression coefficients from the additive model, estimated separately f...

Results of the adjusted linear and logistic regressions (for gender, age and ethnicity) assessing the association between individual measures of socio-economic status and frequency, quantity and binge drinking frequency (n = 57807).

Emma Beard (663085)
Jamie Brown (663086)
Robert West (306586)
Eileen Kaner (588847)
Petra Meier (3183462)
Susan Michie (125435)

February 2019

Results of the adjusted linear and logistic regressions (for gender, age and ethnicity) assessing th...

Results of simple and multivariable logistic regression analyses for male diabetes in Bangladesh.

Md. Mobarak Hossain Khan (439746)
Oliver Gruebner (651933)
Alexander Kraemer (52519)

October 2014

Results of simple and multivariable logistic regression analyses for male diabetes in Bangladesh....

Results of enter and stepwise linear multivariate regression analyses to identify significant predictors of obesity prevalence in females and males.

Wenpeng You (5532983)
Maciej Henneberg (406389)

July 2018

Results of enter and stepwise linear multivariate regression analyses to identify significant pre...

Multiple regression analyses of ISI in relation to subscales of DHI, age, sex, and all groups.

Sung Kyun Kim (4919119)
Ji Hoon Kim (253495)
Seung Sik Jeon (4919122)
Seok Min Hong (2938824)

March 2018

Multiple regression analyses of ISI in relation to subscales of DHI, age, sex, and all groups.</p

Regression analyses of the active behaviour categories, all active behaviours combined and male body size, relative to the total number of offspring sired.

J. Scott Keogh (302800)
Daniel W. A. Noble (314970)
Eleanor E. Wilson (316121)
Martin J. Whiting (284052)

February 2013

Regression analyses of the active behaviour categories, all active behaviours combined and male b...

Percentages for self-rated health, labour force status, financial strain and class and mean for age by country for men.

Richard J. Shaw (30686)
Michaela Benzeval (148855)
Frank Popham (19756)

October 2014

Percentages for self-rated health, labour force status, financial strain and class and mean for a...

Prevalence of demographics and gender equitable attitudes by latent class membership among male participants recruited for UN Multi-Country Study on Men and Violence.

Tiara C. Willie (13864041)
Marina Katague (13864044)
Nafisa Halim (3353189)
Jhumka Gupta (563281)

September 2022

Prevalence of demographics and gender equitable attitudes by latent class membership among male part...

Multivariate Meta-regression Analysis of UAI Prevalence with Any Male Partner.

Jing Wu (54032)
Yifei Hu (569736)
Yujiang Jia (569737)
Yingying Su (229590)
Huixia Cui (409033)
Huixin Liu (569738)
Ning Wang (108353)

May 2014

Multivariate Meta-regression Analysis of UAI Prevalence with Any Male Partner.</p

Multiple regression analyses predicting SOS, BUA and SI for adolescent males.

Mohamed S. Zulfarina (5628941)
Razinah Sharif (5628944)
Syed-Badrul Syarifah-Noratiqah (5628947)
Ahmad M. Sharkawi (5628950)
Zaris-SM Aqilah-SM (5628953)
Sabarul-Afian Mokhtar (5628956)
Shuid A. Nazrun (5628959)
Isa Naina-Mohamed (5628962)

August 2018

Multiple regression analyses predicting SOS, BUA and SI for adolescent males.</p

Meta-regression of (A) percentage male, (B) mean age, and (C) interventions for overall survival.

Chenxi Zhong (388871)
Hongcheng Liu (388872)
Liyan Jiang (388873)
Wei Zhang (405)
Feng Yao (44334)

March 2013

Meta-regression of (A) percentage male, (B) mean age, and (C) interventions for overall survival....

Stratified multivariate analyses of recession indicators (during and after) and mental health indicators for males.

Rada K. Dagher (738599)
Jie Chen (5892)
Stephen B. Thomas (738600)

May 2015

* p ≤ 0.05;** p ≤ 0.01;*** p ≤ 0.001Stratified multivariate analyses of rece...

Results of multiple regression analyses predicting level of participation for females (number of female participants) by economic classification (EC) and GDP (95% confidence intervals for b in parentheses).

Leslie Swartz (162980)
Jason Bantjes (3394580)
Divan Rall (3394583)
Suzanne Ferreira (3394586)
Cheri Blauwet (3394577)
Wayne Derman (3394589)

December 2016

Results of multiple regression analyses predicting level of participation for females (number of ...

Results of multiple regression analyses predicting level of participation for females (number of medals won by female participants) by economic classification (EC) and GDP (95% confidence intervals for b in parentheses).

Leslie Swartz (162980)
Jason Bantjes (3394580)
Divan Rall (3394583)
Suzanne Ferreira (3394586)
Cheri Blauwet (3394577)
Wayne Derman (3394589)

December 2016

Results of multiple regression analyses predicting level of participation for females (number of ...

Logistic regression analysis results for the Male population.

Thomas N. O. Achia (694800)

February 2015

* p<0.05** p<0.01*** p<0.0.Logistic regression analysis results for the Male...

Regression Results: Additive Model with Sex Specific Effects.

Coren L. Apicella (91036)
David Cesarini (123128)
Magnus Johannesson (123135)
Christopher T. Dawes (281512)
Paul Lichtenstein (47559)
Björn Wallace (364028)
Jonathan Beauchamp (364031)
Lars Westberg (364033)

February 2013

Notes: This table reports regression coefficients from the additive model, estimated separately f...

Results of the adjusted linear and logistic regressions (for gender, age and ethnicity) assessing the association between individual measures of socio-economic status and frequency, quantity and binge drinking frequency (n = 57807).

Emma Beard (663085)
Jamie Brown (663086)
Robert West (306586)
Eileen Kaner (588847)
Petra Meier (3183462)
Susan Michie (125435)

February 2019

Results of the adjusted linear and logistic regressions (for gender, age and ethnicity) assessing th...

Results of simple and multivariable logistic regression analyses for male diabetes in Bangladesh.

Md. Mobarak Hossain Khan (439746)
Oliver Gruebner (651933)
Alexander Kraemer (52519)

October 2014

Results of simple and multivariable logistic regression analyses for male diabetes in Bangladesh....

Results of enter and stepwise linear multivariate regression analyses to identify significant predictors of obesity prevalence in females and males.

Wenpeng You (5532983)
Maciej Henneberg (406389)

July 2018

Results of enter and stepwise linear multivariate regression analyses to identify significant pre...

Multiple regression analyses of ISI in relation to subscales of DHI, age, sex, and all groups.

Sung Kyun Kim (4919119)
Ji Hoon Kim (253495)
Seung Sik Jeon (4919122)
Seok Min Hong (2938824)

March 2018

Multiple regression analyses of ISI in relation to subscales of DHI, age, sex, and all groups.</p

Regression analyses of the active behaviour categories, all active behaviours combined and male body size, relative to the total number of offspring sired.

J. Scott Keogh (302800)
Daniel W. A. Noble (314970)
Eleanor E. Wilson (316121)
Martin J. Whiting (284052)

February 2013

Regression analyses of the active behaviour categories, all active behaviours combined and male b...

Percentages for self-rated health, labour force status, financial strain and class and mean for age by country for men.

Richard J. Shaw (30686)
Michaela Benzeval (148855)
Frank Popham (19756)

October 2014

Percentages for self-rated health, labour force status, financial strain and class and mean for a...

Prevalence of demographics and gender equitable attitudes by latent class membership among male participants recruited for UN Multi-Country Study on Men and Violence.

Tiara C. Willie (13864041)
Marina Katague (13864044)
Nafisa Halim (3353189)
Jhumka Gupta (563281)

September 2022

Prevalence of demographics and gender equitable attitudes by latent class membership among male part...

Multivariate Meta-regression Analysis of UAI Prevalence with Any Male Partner.

Jing Wu (54032)
Yifei Hu (569736)
Yujiang Jia (569737)
Yingying Su (229590)
Huixia Cui (409033)
Huixin Liu (569738)
Ning Wang (108353)

May 2014

Multivariate Meta-regression Analysis of UAI Prevalence with Any Male Partner.</p

Multiple regression analyses predicting SOS, BUA and SI for adolescent males.

Mohamed S. Zulfarina (5628941)
Razinah Sharif (5628944)
Syed-Badrul Syarifah-Noratiqah (5628947)
Ahmad M. Sharkawi (5628950)
Zaris-SM Aqilah-SM (5628953)
Sabarul-Afian Mokhtar (5628956)
Shuid A. Nazrun (5628959)
Isa Naina-Mohamed (5628962)

August 2018

Multiple regression analyses predicting SOS, BUA and SI for adolescent males.</p

Meta-regression of (A) percentage male, (B) mean age, and (C) interventions for overall survival.

Chenxi Zhong (388871)
Hongcheng Liu (388872)
Liyan Jiang (388873)
Wei Zhang (405)
Feng Yao (44334)

March 2013

Meta-regression of (A) percentage male, (B) mean age, and (C) interventions for overall survival....

Stratified multivariate analyses of recession indicators (during and after) and mental health indicators for males.

Rada K. Dagher (738599)
Jie Chen (5892)
Stephen B. Thomas (738600)

May 2015

* p ≤ 0.05;** p ≤ 0.01;*** p ≤ 0.001Stratified multivariate analyses of rece...

Results of multiple regression analyses predicting level of participation for males (number of male participants) by economic classification (EC) and GDP (95% confidence intervals for b in parentheses).

Abstract

Extracted data

Results of multiple regression analyses predicting level of participation for males (number of male participants) by economic classification (EC) and GDP (95% confidence intervals for b in parentheses).

Abstract

Extracted data

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