<p>Presented are the percentage of times the 95% multiple imputation intervals contained the true total case enumerations and the width of the imputation based intervals (in units of number of cases), both averaged across the tracts within each region. Results based on the geocoded Maryland Prostate cancer data split into the experimental geocodes and experimental nongeocodes subsets for evaluation.</p
ABSTRACT : BACKGROUND : We consider how representations of geographic variation in prostate cancer i...
Abstract Background As part of a long-term initiative to improve cancer surveillance in New York Sta...
<p>Note: 1. Counties labeled “missing” have incomplete prostate cancer mortality or incidence data. ...
The importance of geography as a source of variation in health research continues to receive sustain...
The importance of geography as a source of variation in health research continues to receive sustain...
Health data usually has missing or incomplete location information, which impacts the quality of res...
Background: The multiple imputation approach to missing data has been validated by a number of simul...
<p>Maryland county level percent of nongeocoded case records (ratio of nongeocoded cases to the tota...
The multiple imputation approach to missing data has been validated by a number of simulation studie...
this paper, we provide more detail on the algorithm than has previously been given and present some ...
Thesis (Master's)--University of Washington, 2019This thesis evaluates the performance of different ...
Abstract Background In response to citizens’ concerns about elevated cancer incidence in their local...
Large complex datasets typically contain large numbers of variables measured on even larger numbers ...
Commonly in survey research, multiple, different analyses are conducted by one or more than one res...
Multiple imputation (MI) has become popular for analyses with missing data in medical research. The ...
ABSTRACT : BACKGROUND : We consider how representations of geographic variation in prostate cancer i...
Abstract Background As part of a long-term initiative to improve cancer surveillance in New York Sta...
<p>Note: 1. Counties labeled “missing” have incomplete prostate cancer mortality or incidence data. ...
The importance of geography as a source of variation in health research continues to receive sustain...
The importance of geography as a source of variation in health research continues to receive sustain...
Health data usually has missing or incomplete location information, which impacts the quality of res...
Background: The multiple imputation approach to missing data has been validated by a number of simul...
<p>Maryland county level percent of nongeocoded case records (ratio of nongeocoded cases to the tota...
The multiple imputation approach to missing data has been validated by a number of simulation studie...
this paper, we provide more detail on the algorithm than has previously been given and present some ...
Thesis (Master's)--University of Washington, 2019This thesis evaluates the performance of different ...
Abstract Background In response to citizens’ concerns about elevated cancer incidence in their local...
Large complex datasets typically contain large numbers of variables measured on even larger numbers ...
Commonly in survey research, multiple, different analyses are conducted by one or more than one res...
Multiple imputation (MI) has become popular for analyses with missing data in medical research. The ...
ABSTRACT : BACKGROUND : We consider how representations of geographic variation in prostate cancer i...
Abstract Background As part of a long-term initiative to improve cancer surveillance in New York Sta...
<p>Note: 1. Counties labeled “missing” have incomplete prostate cancer mortality or incidence data. ...