This study was carried out to use multiple imputation mi in order to correct for the potential nonresponse bias in measurements related to variable fasting blood glucose fbs in noncommunicable disease risk factors survey conducted in iran in 2007. Multiple imputation for nonresponse when estimating hiv prevalence using survey data amos chinomona1,2 and henry mwambi2 abstract background. Wilson 1 andkerstinlueck 2,3 department of public health sciences, division of biostatis tics, university of california, davis, davis, ca, usa. Multiple imputation of family income and personal earnings in. A twostage imputation procedure for item nonresponse in. The accessible style of estimation in surveys with nonresponse will make this an invaluable tool for survey methodologists in national statistics agencies and private survey agencies. Multiple imputation for nonresponse in surveys donald b. Multiple imputation in the survey of consumer finances. Multiple imputation, unit nonresponse, missing data, complex surveys.
Multiple imputation for combinedsurvey estimation with. We develop a method for constructing a monotone missing pattern that allows for imputation of. A randomized controlled trial of an internetbased intervention for. Leone university of texas at austin regardless of the overall response rate, surveys that involve individual self. Using matched substitutes to adjust for nonignorable nonresponse through multiple imputations d. Fractional imputation fi is a relatively new method of imputation for handling item nonresponse in survey sampling. Missing data analysis multiple imputation, em method. Multiple imputation for nonresponse in surveys wiley. In the case of unit nonresponse, we often have limited data on nonrespondents. In longitudinal studies for some missing values there might be past or future data points available. Using administrative records to impute for nonresponse e. The goal was to facilitate valid inferences when the data producer and the. The multiple imputation procedure was performed using markov chain monte carlo mcmc methods making use of an iterative data augmentation technique as explained by. When substituting for a data point, it is known as unit imputation.
Multiple imputation for nonresponse when estimating hiv prevalence using survey data article pdf available in bmc public health 151. For example, in astrophysics, properties of hardly observable, distant. Jrp remotely monitored gamification and social incentives to. For each of the 20 imputed data sets, a different value has been imputed for bmi. Imputation for nonresponse using the annual financial. High nonresponse rates are of theoretical and practical importance, because of the need to justify the high survey costs of random samples compared with convenience. Oct 16, 2015 missing data are a common feature in many areas of research especially those involving survey data in biological, health and social sciences research.
Clearly illustrates the advantages of modern computing to such handle surveys, and demonstrates the benefit of this statistical technique for researchers who must analyze them. Bridging a survey redesign using multiple imputation. In particular, as described by, the basic setup of the multiple imputation procedure in mi involves three steps. Also presents the background for bayesian and frequentist theory. The data used in this paper are from the most recent nsre survey 19992007. Summary of multiple imputation retains advantages of single imputation consistent analyses data collectors knowledge rectangular data sets corrects disadvantages of single imputation reflects uncertainty in imputed values corrects inefficiency from imputing draws estimates have high efficiency for modest m, e.
In addition, many of the assets and liabilities treated in the survey. Oct 16, 2015 the multiple imputation procedure was performed using markov chain monte carlo mcmc methods making use of an iterative data augmentation technique as explained by. Owing to the perceived sensitivity of this topic to some people, unit and item nonresponse rates in the scf are substantial. Multiple imputation techniques were used to account for missingness at the item level and. The imputation procedures used for sipp are based on the assumption that data are missing at random within subgroups of the population. Frontmatter multiple imputation for nonresponse in surveys. The statistical goal of imputation is to reduce the bias of survey estimates. Multiple imputation for nonresponse in surveys published online. Multiple imputation rubins 1987a multiple imputation methodology first requires a model for producing proper imputed values. Multiple imputation of family income and personal earnings in the national health interview survey. The trends toward declining survey response rates that are documented in chapter 1 have consequences. Multiple imputation to correct for nonresponse bias. Webbased fully automated selfhelp with different levels of.
Although some experts advised that unless nonresponse rate is not unusually high more than five to ten imputation has no additional gain in efficiency rubin, 1987. It is also known as fully conditional specification and, sequential regression. To illustrate the method, we used data from the canadian multicentre osteoporosis study, a large cohort study of 9423 randomly selected canadians, designed in part to estimate the prevalence of osteoporosis. Simpler imputation methods as well as more advanced methods, such as fractional and multiple imputation, are considered. The imputation of missing data is often a crucial step in the analysis of survey data.
Frontmatter multiple imputation for nonresponse in. Multiple imputation to account for missing data in a survey. After the imputation process, they are often treated like originally observed values, leading to an underestimation of the variance in the data and from this to p values that are too significant. Pdf multiple imputation for nonresponse in surveys semantic. Multiple imputation of family income and personal earnings. May 26, 2004 buy multiple imputation for nonresponse in surveys wiley classics library subsequent by rubin, donald b. Multiple imputation was suggested by rubin 1978 to overcome these problems. Multiple imputation for unit nonresponse and measurement. The study protocol can be downloaded from the following website. Researchers, teachers, and students of statistics, social sciences and economics will benefit from the clear presentation and numerous examples. Missing data are a common feature in many areas of research especially those involving survey data in biological, health and social sciences research. One key consequence is that high nonresponse rates undermine the rationale for inference in probabilitybased surveys, which is that the respondents constitute a random selection from the target population.
Most of the analyses of the survey data are done taking a completecase approach, that is taking a listwise deletion of all cases with missing values assuming that missing values are missing completely at random mcar. Instead of filling in a single value for each missing value, rubins 1987 multiple imputation procedure replaces each missing value with a set of plausible values that represent the uncertainty about the right value to. Multiple imputation provides a useful strategy for dealing with data sets with missing values. Everyday low prices and free delivery on eligible orders. While nonresponse to the manifest items is a common complication, inferences of lcr can be evaluated using maximum likelihood, multiple imputation, and twostage multiple imputation. Multiple imputation for multiple surveys department of statistics. Featback was offered with or without chat, skype, or email support from a therapist, which. Multiple imputation methods have several advantages over completecase analyses or single imputation. Multiple imputation to account for missing data in a. Multiple imputation can be used in cases where the data is missing completely at random, missing at random, and even when the data is missing not at random.
This goal is achieved to the extent that systematic patterns of item nonresponse are correctly identified and modeled. However, the primary method of multiple imputation is multiple imputation by chained equations mice. Grabka, diw berlin abstract statistical analysis in surveys is generally facing missing data. The goal was to facilitate valid inferences when the data producer and the ultimately many end users of the data were distinct entities. Multiple imputation methodology for missing data, non. Journal of the american statistical association, 93, pp. Multiple imputation for nonresponse in surveys wiley series. Multiple imputation for nonresponse when estimating hiv. Adjusting for nonresponse in the analysis stage might lead different analysts to use different, and inconsistent, adjustment methods.
Imputation methods for handling item nonresponse in the. The nonresponse, in the form of either unit or item. Multiple imputation background most large scale surveys are subject to some nonresponse. A ndy p eytchev is a survey methodologist at rti international, research triangle park, nc, usa, and an instructor at the odum institute, university of north carolina at chapel hill, chapel hill, nc, usa. This means that the imputation model can be optimized in such a way that it strongly predicts both the dependent variable to be imputed, and the missingness process. This video introduces basic concept in missing data imputation including mean, regression, indication and em method of single imputation and multiple imputation. Multiple imputation for nonresponse in surveys wiley series in probability and statistics. Demonstrates how nonresponse in sample surveys and censuses can be handled by replacing each missing value with two or more multiple imputations. Withinsurvey multiple imputation mi methods are adapted to pooledsurvey regression estimation where one survey has a larger set of regressors but fewer observations than the other. With incomplete regressors in one but not both surveys. The survey of consumer finances scf focuses intensely on the details of households finances. Imputation for nonresponse using the annual financial statistics survey by smeeta singh submitted in fulfilment of the requirements for the degree of master of science, in the school of statistics and actuarial science at the university of kwazulunatal.
The imputation of multiple plausible values will let the estimation procedure take into account the fact that the true value is unknown and hence uncertain. Multiple imputation is used to create values for missing family income data in the national survey on recreation and the environment. In statistics, imputation is the process of replacing missing data with substituted values. Inferences for twostage multiple imputation for nonresponse. The paper introduces the reader new to the imputation literature to key ideas and methods. In fi, several imputed values with their fractional weights are created for each. There are three main problems that missing data causes. Taylor 1996 partially parametric techniques for multiple imputation. Using an appropriate method to handle cases with missing data when performing secondary analyses of survey data is important to reduce bias and to reach. Multiple imputation for nonresponse in surveys wiley series in. Issues of nonresponse and imputation in the survey of income and program participation graham kalton university of michigan daniel kasprzyk department of health and human services robert santos university of michigan this paper describes the extent and nature of the household, person and itemlevel nonresponse that the u. We present an overview of the survey and a description of the missingness pattern for family income and other key variables. Pdf multiple imputation for nonresponse when estimating. To provide the same complete data to all the analysts, you can impute the missing values by replacing them with reasonable nonmissing values.