Health Outcomes Research

Author(s):  
Sheina Orbell ◽  
Havah Schneider ◽  
Sabrina Esbitt ◽  
Jeffrey S. Gonzalez ◽  
Jeffrey S. Gonzalez ◽  
...  
2007 ◽  
Vol 16 (S1) ◽  
pp. 175-186 ◽  
Author(s):  
Bryce B. Reeve ◽  
Laurie B. Burke ◽  
Yen-pin Chiang ◽  
Steven B. Clauser ◽  
Lisa J. Colpe ◽  
...  

2018 ◽  
Vol 4 (4) ◽  
pp. 367-378 ◽  
Author(s):  
S. Hassan ◽  
T. Ojo ◽  
D. Galusha ◽  
J. L. Martinez-Brockman ◽  
O. P. Adams ◽  
...  

Author(s):  
Patricia Cerrito ◽  
John Cerrito

Many of the datasets provided by the federal government have been well cleaned. However, like many other datasets collected for health outcomes research, these datasets contain errors and missing values. Both errors and missing values should be accommodated unless they represent less than 5% of the total values in the dataset. If the proportion of missing values is greater, then it is necessary to accommodate them in some way; otherwise, the missing values can impact the outcome of the study. Errors are more difficult to work with because it is not possible to know just what the proportion of errors actually is. In this chapter, we examine both errors and missing values and provide some techniques on how to investigate them.


2017 ◽  
Vol 120 (1-2) ◽  
pp. S94
Author(s):  
Blanca Medrano Engay ◽  
Ana Roy ◽  
Koldo Atutxa ◽  
Vicente Diaz-Morant ◽  
Javier Garcia-Frade ◽  
...  

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Andrew Grundy ◽  
Anju Devianee Keetharuth ◽  
Rosemary Barber ◽  
Jill Carlton ◽  
Janice Connell ◽  
...  

2009 ◽  
Vol 12 (3) ◽  
pp. A34
Author(s):  
SL Szeinbach ◽  
AP Beyer ◽  
ZP Qureshi ◽  
AA Uhas ◽  
J Visaria ◽  
...  

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