Informações sobre o curso
3.8
73 classificações
18 avaliações
100% online

100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Horas para completar

Aprox. 9 horas para completar

Sugerido: 4 weeks of study, 1-2 hours/week...
Idiomas disponíveis

Inglês

Legendas: Inglês
100% online

100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Horas para completar

Aprox. 9 horas para completar

Sugerido: 4 weeks of study, 1-2 hours/week...
Idiomas disponíveis

Inglês

Legendas: Inglês

Programa - O que você aprenderá com este curso

Semana
1
Horas para completar
3 horas para concluir

General Steps in Weighting

Weights are used to expand a sample to a population. To accomplish this, the weights may correct for coverage errors in the sampling frame, adjust for nonresponse, and reduce variances of estimators by incorporating covariates. The series of steps needed to do this are covered in Module 1....
Reading
7 vídeos (total de (Total 48 mín.) min), 7 leituras, 7 testes
Video7 videos
Quantities to Estimate8min
Goals of Estimation6min
Statistical Interpretation of Estimates10min
Coverage Problems5min
Improving Precision3min
Effects of Weighting on SEs2min
Reading7 leituras
Class notes + additional reading10min
Class notes10min
Class Notes10min
Class Notes10min
Class Notes10min
Class Notes10min
Class Notes10min
Quiz7 exercícios práticos
Introductory quiz on weights6min
Quantities4min
Goals6min
Interpretation6min
Coverage4min
Improving precision6min
Effects on SEs6min
Semana
2
Horas para completar
2 horas para concluir

Specific Steps

Specific steps in weighting include computing base weights, adjusting if there are cases whose eligibility we are unsure of, adjusting for nonresponse, and using covariates to calibrate the sample to external population controls. We flesh out the general steps with specific details here....
Reading
6 vídeos (total de (Total 44 mín.) min), 6 leituras, 5 testes
Video6 videos
Base Weights8min
Nonresponse Adjustments7min
Response Propensities4min
Tree algorithms10min
Calibration5min
Reading6 leituras
Class Notes10min
Class Notes10min
Class Notes10min
Class Notes10min
Class Notes10min
Class Notes10min
Quiz5 exercícios práticos
Overview6min
Base weights6min
Nonresponse4min
Trees4min
Calibration6min
Semana
3
Horas para completar
2 horas para concluir

Implementing the Steps

Software is critical to implementing the steps, but the R system is an excellent source of free routines. This module covers several R packages, including sampling, survey, and PracTools that will select samples and compute weights....
Reading
6 vídeos (total de (Total 64 mín.) min), 5 leituras, 4 testes
Video6 videos
Base Weights10min
More on Base Weights13min
Nonresponse Adjustments13min
Examples of Calibration7min
Software for Poststratification14min
Reading5 leituras
Class Notes10min
Class Notes + Software10min
Class Notes10min
Class Notes + Software for propensity classes10min
Class Notes + Software for calibration10min
Quiz4 exercícios práticos
Software4min
Quiz on base weights8min
Quiz on nonresponse adjustments6min
Quiz on calibration and poststratification8min
Semana
4
Horas para completar
2 horas para concluir

Imputing for Missing Items

In most surveys there will be items for which respondents do not provide information, even though the respondent completed enough of the data collection instrument to be considered "complete". If only the cases with all items present are retained when fitting a model, quite a few cases may be excluded from the analysis. Imputing for the missing items avoids dropping the missing cases. We cover methods of doing the imputing and of reflecting the effects of imputations on standard errors in this module....
Reading
6 vídeos (total de (Total 46 mín.) min), 5 leituras, 5 testes
Video6 videos
Means and hotdeck7min
Regression Imputation6min
Effect on Variances9min
mice R package4min
mice example10min
Reading5 leituras
Class Notes10min
Class Notes10min
Class Notes10min
Class Notes10min
Class Notes + mice R package10min
Quiz5 exercícios práticos
Reasons for imputing6min
Means and hot deck4min
Regression imputation8min
Effects on variances8min
Imputation software12min
Horas para completar
13 minutos para concluir

Summary of Course 5

We briefly summarize the methods of weighting and imputation that were covered in Course 5....
Reading
1 vídeo (total de (Total 3 mín.) min), 1 leitura
Video1 vídeos
Reading1 leituras
Class Notes10min
3.8
18 avaliaçõesChevron Right

Melhores avaliações

por MMJun 5th 2017

This course quite help to get as much reliable data as possible for any survey.

Instrutores

Avatar

Richard Valliant, Ph.D.

Research Professor
Joint Program in Survey Methodology

Sobre University of Maryland, College Park

The University of Maryland is the state's flagship university and one of the nation's preeminent public research universities. A global leader in research, entrepreneurship and innovation, the university is home to more than 37,000 students, 9,000 faculty and staff, and 250 academic programs. Its faculty includes three Nobel laureates, three Pulitzer Prize winners, 47 members of the national academies and scores of Fulbright scholars. The institution has a $1.8 billion operating budget, secures $500 million annually in external research funding and recently completed a $1 billion fundraising campaign. ...

Sobre o Programa de cursos integrados Survey Data Collection and Analytics

This specialization covers the fundamentals of surveys as used in market research, evaluation research, social science and political research, official government statistics, and many other topic domains. In six courses, you will learn the basics of questionnaire design, data collection methods, sampling design, dealing with missing values, making estimates, combining data from different sources, and the analysis of survey data. In the final Capstone Project, you’ll apply the skills learned throughout the specialization by analyzing and comparing multiple data sources. Faculty for this specialisation comes from the Michigan Program in Survey Methodology and the Joint Program in Survey Methodology, a collaboration between the University of Maryland, the University of Michigan, and the data collection firm Westat, founded by the National Science Foundation and the Interagency Consortium of Statistical Policy in the U.S. to educate the next generation of survey researchers, survey statisticians, and survey methodologists. In addition to this specialization we offer short courses, a summer school, certificates, master degrees as well as PhD programs....
Survey Data Collection and Analytics

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.

Mais dúvidas? Visite o Central de Ajuda ao Aprendiz.