This course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration. Among the techniques discussed are adjustments using estimated response propensities, poststratification, raking, and general regression estimation. Alternative techniques for imputing values for missing items will be discussed. For both weighting and imputation, the capabilities of different statistical software packages will be covered, including R®, Stata®, and SAS®.
Este curso forma parte de Programa Especializado - Survey Data Collection and Analytics
ofrecido por
Programa Especializado - Survey Data Collection and Analytics Universidad de Maryland en College ParkAcerca de este Curso
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Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Aprox. 18 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Aprox. 18 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
ofrecido por
Universidad de Maryland en 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.
Programa - Qué aprenderás en este curso
5 horas para completar
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.
5 horas para completar
7 videos (Total 48 minutos), 7 lecturas, 7 cuestionarios
7 videos
Introduction10m
Quantities to Estimate8m
Goals of Estimation6m
Statistical Interpretation of Estimates10m
Coverage Problems5m
Improving Precision3m
Effects of Weighting on SEs2m
7 lecturas
Class notes + additional reading10m
Class notes10m
Class Notes10m
Class Notes10m
Class Notes10m
Class Notes10m
Class Notes10m
7 ejercicios de práctica
Introductory quiz on weights30m
Quantities30m
Goals30m
Interpretation30m
Coverage30m
Improving precision30m
Effects on SEs30m
4 horas para completar
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.
4 horas para completar
6 videos (Total 44 minutos), 6 lecturas, 5 cuestionarios
6 videos
Overview7m
Base Weights8m
Nonresponse Adjustments7m
Response Propensities4m
Tree algorithms10m
Calibration5m
6 lecturas
Class Notes10m
Class Notes10m
Class Notes10m
Class Notes10m
Class Notes10m
Class Notes10m
5 ejercicios de práctica
Overview30m
Base weights30m
Nonresponse30m
Trees30m
Calibration30m
4 horas para completar
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.
4 horas para completar
6 videos (Total 64 minutos), 5 lecturas, 4 cuestionarios
6 videos
Software4m
Base Weights10m
More on Base Weights13m
Nonresponse Adjustments13m
Examples of Calibration7m
Software for Poststratification14m
5 lecturas
Class Notes10m
Class Notes + Software10m
Class Notes10m
Class Notes + Software for propensity classes10m
Class Notes + Software for calibration10m
4 ejercicios de práctica
Software30m
Quiz on base weights30m
Quiz on nonresponse adjustments30m
Quiz on calibration and poststratification30m
4 horas para completar
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.
4 horas para completar
6 videos (Total 46 minutos), 5 lecturas, 5 cuestionarios
6 videos
Means and hotdeck7m
Regression Imputation6m
Effect on Variances9m
mice R package4m
mice example10m
5 lecturas
Class Notes10m
Class Notes10m
Class Notes10m
Class Notes10m
Class Notes + mice R package10m
5 ejercicios de práctica
Reasons for imputing30m
Means and hot deck30m
Regression imputation30m
Effects on variances30m
Imputation software30m
13 minutos para completar
Summary of Course 5
We briefly summarize the methods of weighting and imputation that were covered in Course 5.
13 minutos para completar
1 video (Total 3 minutos), 1 lectura
1 video
Summary2m
1 lectura
Class Notes10m
Reseñas
Principales reseñas sobre DEALING WITH MISSING DATA
por SS18 de nov. de 2017
This course was hard to follow, hard to complete (quizzes), poorly designed and with little useful content. In other words, not worth the money I paid for it!
por MN13 de abr. de 2017
Aside from a little hiccup with one of the quiz questions during week 1, this course was worth my time.
por ZM19 de ago. de 2019
interesting material, well taught, lots of short quizzes to enforce understanding.
por MM4 de jun. de 2017
This course quite help to get as much reliable data as possible for any survey.
Acerca de Programa especializado: 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.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
El acceso a las clases y las asignaciones depende del tipo de inscripción que tengas. Si tomas un curso en modo de oyente, verás la mayoría de los materiales del curso en forma gratuita. Para acceder a asignaciones calificadas y obtener un certificado, deberás comprar la experiencia de Certificado, ya sea durante o después de participar como oyente. Si no ves la opción de oyente:
- es posible que el curso no ofrezca la opción de participar como oyente. En cambio, puedes intentar con una Prueba gratis o postularte para recibir ayuda económica.
- Es posible que el curso ofrezca la opción 'Curso completo, sin certificado'. Esta opción te permite ver todos los materiales del curso, enviar las evaluaciones requeridas y obtener una calificación final. También significa que no podrás comprar una experiencia de Certificado.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
Is financial aid available?
Sí, Coursera ofrece ayuda económica a los estudiantes que no pueden pagar la tarifa. Solicítala haciendo clic en el enlace de Ayuda económica que está debajo del botón “Inscribirse” a la izquierda. Se te pedirá que completes una solicitud. Recibirás una notificación en caso de que se apruebe. Deberás completar este paso para cada uno de los cursos que forman parte del Programa especializado, incluido el proyecto final. Obtén más información.
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