Ryan T Moore Dataverse

Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

1 to 10 of 67 Results

Replication data for: Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom Jan 5, 2015 Moore, Ryan T., 2014, "Replication data for: Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom", https://doi.org/10.7910/DVN/26685, Harvard Dataverse, V2, UNF:5:eW5o4A7CXYkLrS9ZtaKvmg== [fileUNF] The included file replication.R performs calculations and simulations to replicate the results of Moore, Ryan T. ``Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom''. PS: Political Science & Politics, 48(1):149-156, 2015.
Replication data for: Multivariate Continuous Blocking to Improve Political Science Experiments Oct 2, 2014 - Political Analysis Dataverse Ryan Moore, 2012, "Replication data for: Multivariate Continuous Blocking to Improve Political Science Experiments", https://doi.org/10.7910/DVN/I8RK9Q, Harvard Dataverse, V2, UNF:5:wSC3BTd3JRzXJO9M4SEMOw== [fileUNF] Political scientists use randomized treatment assignments to aid causal inference in field experiments, psychological laboratories, and survey research. Political research can do considerably better than completely randomized designs, but few political science experiments combine random treatment assignment with blocking on a rich set of background...
class1.tab Jul 31, 2014 - Replication data for: Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom Tabular Data - 541 B - 2 Variables, 38 Observations - UNF:5:Ogd+yglMXUGVfJOj9hbyAw== data Data for American politics class example
class2.tab Jul 31, 2014 - Replication data for: Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom Tabular Data - 731 B - 7 Variables, 41 Observations - UNF:5:vvN4VbHLV+kvLIYRJlEiFA== data Data for methodology class example
drawGroups.R Jul 31, 2014 - Replication data for: Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom Plain Text - 2.2 KB - MD5: 53896bfdcc834513ec416a52b119a85a code Creates data sets and calculates summary statistics for simulated examples of 24 students
evaluateLabs.R Jul 31, 2014 - Replication data for: Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom Plain Text - 2.7 KB - MD5: 8592c58830f185c439f25cc62d38fc40 code Loads data and performs calculations for methodology class application in Section 5.3
README.txt Jul 31, 2014 - Replication data for: Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom Plain Text - 1.9 KB - MD5: 14d2e186c002473479efdc97c9cf1ffd README Documents included code and data
replication.R Jul 31, 2014 - Replication data for: Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom Plain Text - 7.5 KB - MD5: 380510c20866eac7b2a33a002ed852a8 code Performs primary calculations and simulations
Replication data for: Public Policy for the Poor? A Randomised Assessment of the Mexican Universal Health Insurance Programme May 26, 2014 - Gary King Dataverse Gary King; Emmanuela Gakidou; Kosuke Imai; Jason Lakin; Ryan T. Moore; Clayton Nall; Nirmala Ravishankar; Manett Vargas; Martha María Téllez-Rojo; Juan Eugenio Hernández-Ávila; Mauricio Hernández-Ávila; Hector Hernández Llamas, 2009, "Replication data for: Public Policy for the Poor? A Randomised Assessment of the Mexican Universal Health Insurance Programme", https://doi.org/10.7910/DVN/P6NC0M, Harvard Dataverse, V6, UNF:3:jeUN9XODtYUp2iUbe8gWZQ== [fileUNF] Background: We assessed aspects of Seguro Popular, a programme aimed to deliver health insurance, regular and preventive medical care, medicines, and health facilities to 50 million uninsured Mexicans. Methods: We randomly assigned treatment within 74 matched pairs of health clusters–-i.e., health facility catchment areas–-representing 118,569 hous...
Replication data for: Driving Support: Workers, PACs, and Congressional Support of the Auto Industry Sep 8, 2013 Moore, Ryan T; Powell, Eleanor Neff; Reeves, Andrew, 2013, "Replication data for: Driving Support: Workers, PACs, and Congressional Support of the Auto Industry", https://doi.org/10.7910/DVN/DWNIJY, Harvard Dataverse, V1 These files provide a guide to the code and data objects associated with Moore, Ryan T., Eleanor Neff Powell, and Andrew Reeves. "Driving Support: Workers, PACs, and Congressional Support of the Auto Industry". Business and Politics, 15(2):137-162, 2013.

Replication data for: Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom

Jan 5, 2015

Moore, Ryan T., 2014, "Replication data for: Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom", https://doi.org/10.7910/DVN/26685, Harvard Dataverse, V2, UNF:5:eW5o4A7CXYkLrS9ZtaKvmg== [fileUNF]

The included file replication.R performs calculations and simulations to replicate the results of Moore, Ryan T. ``Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom''. PS: Political Science & Politics, 48(1):149-156, 2015.

Replication data for: Multivariate Continuous Blocking to Improve Political Science Experiments

Oct 2, 2014 - Political Analysis Dataverse

Ryan Moore, 2012, "Replication data for: Multivariate Continuous Blocking to Improve Political Science Experiments", https://doi.org/10.7910/DVN/I8RK9Q, Harvard Dataverse, V2, UNF:5:wSC3BTd3JRzXJO9M4SEMOw== [fileUNF]

Political scientists use randomized treatment assignments to aid causal inference in field experiments, psychological laboratories, and survey research. Political research can do considerably better than completely randomized designs, but few political science experiments combine random treatment assignment with blocking on a rich set of background...

class1.tab

Jul 31, 2014 - Replication data for: Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom

Tabular Data - 541 B - 2 Variables, 38 Observations -

data

Data for American politics class example

class2.tab

Jul 31, 2014 - Replication data for: Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom

Tabular Data - 731 B - 7 Variables, 41 Observations -

data

Data for methodology class example

drawGroups.R

Jul 31, 2014 - Replication data for: Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom

Plain Text - 2.2 KB -

code

Creates data sets and calculates summary statistics for simulated examples of 24 students

evaluateLabs.R

Jul 31, 2014 - Replication data for: Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom

Plain Text - 2.7 KB -

code

Loads data and performs calculations for methodology class application in Section 5.3

README.txt

Jul 31, 2014 - Replication data for: Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom

Plain Text - 1.9 KB -

README

Documents included code and data

replication.R

Jul 31, 2014 - Replication data for: Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom

Plain Text - 7.5 KB -

code

Performs primary calculations and simulations

Replication data for: Public Policy for the Poor? A Randomised Assessment of the Mexican Universal Health Insurance Programme

May 26, 2014 - Gary King Dataverse

Gary King; Emmanuela Gakidou; Kosuke Imai; Jason Lakin; Ryan T. Moore; Clayton Nall; Nirmala Ravishankar; Manett Vargas; Martha María Téllez-Rojo; Juan Eugenio Hernández-Ávila; Mauricio Hernández-Ávila; Hector Hernández Llamas, 2009, "Replication data for: Public Policy for the Poor? A Randomised Assessment of the Mexican Universal Health Insurance Programme", https://doi.org/10.7910/DVN/P6NC0M, Harvard Dataverse, V6, UNF:3:jeUN9XODtYUp2iUbe8gWZQ== [fileUNF]

Background: We assessed aspects of Seguro Popular, a programme aimed to deliver health insurance, regular and preventive medical care, medicines, and health facilities to 50 million uninsured Mexicans. Methods: We randomly assigned treatment within 74 matched pairs of health clusters–-i.e., health facility catchment areas–-representing 118,569 hous...

Replication data for: Driving Support: Workers, PACs, and Congressional Support of the Auto Industry

Sep 8, 2013

Moore, Ryan T; Powell, Eleanor Neff; Reeves, Andrew, 2013, "Replication data for: Driving Support: Workers, PACs, and Congressional Support of the Auto Industry", https://doi.org/10.7910/DVN/DWNIJY, Harvard Dataverse, V1

These files provide a guide to the code and data objects associated with Moore, Ryan T., Eleanor Neff Powell, and Andrew Reeves. "Driving Support: Workers, PACs, and Congressional Support of the Auto Industry". Business and Politics, 15(2):137-162, 2013.

Add Data

Share Dataverse

Link Dataverse

Reset Modifications