1998 Ohio Family Health Survey 
Data Usage Notes

Ohio Department of Health
Center for Public Health Data and Statistics

1.  Merging Adult and Child Data:  The Ohio Family Health Survey data includes separate data sets for adults and children. Many household and family level variables are on the adult but not the child data sets.  The variable “IDNO” is included in both data sets and is unique to each household, meaning that adults and children from the same household share the same value of IDNO.  Therefore, the adult and child data sets may be merged or linked by “IDNO” to analyze adults and children together or assign family and household level variables to children.  

2. Sampling Variability and Reliability of Estimates: Estimates derived from subsets of the Ohio Family Health Survey may not be accurate due to high sampling variability.  Using such estimates inappropriately can result in the presentation of misleading information or unwarranted comparisons between population groups.  The Ohio Department of Health recommends that estimates be presented with indicators of variance such as standard errors or confidence intervals, and that differences between populations not be assumed without testing for statistical significance.  Specialized survey analysis software (such as SUDAAN, WESVAR, or STATA) is needed to calculate standard errors or confidence intervals because the Ohio Family Health Survey did not have a simple random sample design.  The survey design included stratification by counties and clustering within households.  Many common versions of standard spreadsheet and statistical software packages (such as EXCEL and SAS) should not be used to calculate variance because their formulas assume a simple random sample and do not allow users to input survey design statements. See the “Design Statements” file for examples of specific design statements that may be used.

3. Missing Employment Data: Due to a skip pattern error in the questionnaire, 601 workers who said that their employer did not offer health insurance were not asked a series of questions regarding their hours worked, class of work, industry, county of work, and size of employer.  These questions were also not asked of 41 respondents who said they did not know whether their employer offered insurance.  Since the missing data is not random, employment-related analyses not taking into account these missing values may produce misleading results.  For instance, not adjusting for missing data would result in:

A.	Overestimation of employer health insurance offer rates since most respondents with missing employment data were not offered insurance. 
B.	Underestimation of the prevalence of part-time workers, workers in retail, and workers in small firms since such workers were less likely to be offered insurance, and therefore more likely to not be asked the employment questions. 
C.	Underestimation of uninsured rates by employment characteristic since workers not offered insurance by their employer were more likely to be uninsured.  The underestimation would be most severe for the worker characteristics most likely to not be offered insurance (part-time workers, workers in retail, and workers in small firms).
One method of adjusting for the missing employment data is to use redistributed weights.  The supplemental data set “Employwt” includes revised weights that were redistributed from the 642 respondents with missing data to 1213 other respondents with similar characteristics.   These weights may be used to adjust employment information for those not offered insurance to the correct population size.  The weights may be linked or merged with the adult data set using the “IDNO” variable.   See Redistribution of Weights for Missing Employment Data from the Ohio Family Health Survey, SH Woodard, Ph.D., Biostatistics Program, The Ohio State University, June 2000 for further details.  

4. Recommended Citation: Any published material should cite the 1998 Ohio Family Health Survey, Ohio Department of Health, Center for Public Health Data and Statistics as source data while indicating that the analysis, interpretations, or conclusions reached are those of the author.

5. Additional Information: For additional information about missing employment data and appropriate use of the data, please see the Methodology Report included along with data set documentation.