This dataset represents a probability sample derived from the
1999–2010 cycles of the National Health and Nutrition
Examination Survey (NHANES). It is used as a probability
reference survey to support the pseudo-weighting methods
implemented in the nonprobsampling package.
Usage
data(sp1)Format
A data frame with 3494 observations and 14 variables:
- agecat
Age category (factor with 4 levels: 1 = 55–59, 2 = 60–64, 3 = 65–69, 4 = 70+)
- marital
Marital status (factor with 4 levels: 1 = Married Or Living As Married, 2 = Widowed, 3 = Divorced or Separated, 4 = Never Married)
- race
Race category (factor with 4 levels: 1 = White, 2 = Black, 3 = Hispanic, 4 = Other)
- education
Education level (factor with 5 levels: 1 = Less Than 8 Years, 2 = 8–11 Years, 3 = 12 Years Or Completed High School, 4 = College Graduate, 5 = Postgraduate)
- employment
Employment status (factor with 2 levels: 0 = Not Working, 1 = Working)
- smoking
Smoking status (factor with 3 levels: 1 = Never Smoker, 2 = Former Smoker, 3 = Current Smoker)
- comorbidity
General comorbidity indicator (factor with 2 levels: 0 = No, 1 = Yes)
- psa_level
Serum prostate-specific antigen level (numeric)
- BMI
Body mass index category (factor with 4 levels: "Normal", "Overweight", "Obese", "Morbidly Obese")
- diabetes
Diabetes diagnosis indicator (factor with 2 levels: 0 = No, 1 = Yes)
- pros_enlarged
Prostate enlargement indicator (factor with 2 levels: 0 = No, 1 = Yes)
- strata_sp1
Stratum identifier for complex survey design (numeric)
- psu_sp1
Primary sampling unit identifier for complex survey design (numeric)
- wts_sp1
10-year interview sampling weights (numeric)
Source
Derived from the National Health and Nutrition Examination Survey (NHANES), 1999–2010 cycles, conducted by the U.S. National Center for Health Statistics (NCHS).
Details
The dataset includes auxiliary variables shared with the nonprobability
sample sc, enabling the construction of pseudo-weights to adjust
for participation bias. Survey design variables and sampling weights are
provided to support design-consistent estimation.
The sp1 dataset
contains the outcome variable psa_level, which is also observed in
sc, allowing for the evaluation of pseudo-weighted estimators against
estimates based on true sampling weights. It may also be incorporated into
the participation model, potentially enhancing bias reduction when
participation depends on the outcome.
Examples
data(sp1)
str(sp1)
#> 'data.frame': 3494 obs. of 14 variables:
#> $ agecat : Factor w/ 4 levels "1","2","3","4": 4 2 4 3 2 2 1 1 4 3 ...
#> $ marital : Factor w/ 4 levels "1","2","3","4": 1 3 1 1 1 1 1 1 1 1 ...
#> $ race : Factor w/ 4 levels "1","2","3","4": 3 1 3 3 1 1 1 1 1 1 ...
#> $ education : Factor w/ 5 levels "1","2","3","4",..: 1 3 2 3 3 2 2 4 5 2 ...
#> $ employment : Factor w/ 2 levels "0","1": 1 1 1 1 1 1 2 2 1 1 ...
#> $ smoking : Factor w/ 3 levels "1","2","3": 2 2 2 2 2 2 2 1 3 2 ...
#> $ comorbidity : Factor w/ 2 levels "0","1": 2 2 1 2 2 1 2 1 2 1 ...
#> $ psa_level : num NA NA NA NA NA NA NA NA NA NA ...
#> $ BMI : Factor w/ 4 levels "Morbidly Obese",..: 2 3 4 3 4 3 4 4 2 4 ...
#> $ diabetes : Factor w/ 2 levels "0","1": 2 2 1 2 1 1 2 1 1 1 ...
#> $ pros_enlarged: Factor w/ 2 levels "0","1": 2 1 1 2 1 2 1 1 2 1 ...
#> $ strata_sp1 : int 13 12 6 13 5 12 10 11 1 7 ...
#> $ psu_sp1 : int 2 2 1 2 2 1 1 1 2 1 ...
#> $ wts_sp1 : num 401 8923 481 498 9314 ...
summary(sp1)
#> agecat marital race education employment smoking comorbidity
#> 1: 697 1:2665 1:1762 1:743 0:2057 1:1097 0:1286
#> 2:1074 2: 182 2: 747 2:574 1:1437 2:1582 1:2208
#> 3: 879 3: 469 3: 880 3:742 3: 815
#> 4: 844 4: 178 4: 105 4:707
#> 5:728
#>
#>
#> psa_level BMI diabetes pros_enlarged strata_sp1
#> Min. : 0.070 Morbidly Obese: 324 0:2744 0:2699 Min. : 1.00
#> 1st Qu.: 0.670 Normal : 891 1: 750 1: 795 1st Qu.:17.00
#> Median : 1.215 Obese : 748 Median :36.00
#> Mean : 2.133 Overweight :1531 Mean :36.81
#> 3rd Qu.: 2.340 3rd Qu.:58.00
#> Max. :72.540 Max. :74.00
#> NA's :1190
#> psu_sp1 wts_sp1
#> Min. :1.00 Min. : 346.4
#> 1st Qu.:1.00 1st Qu.: 1841.4
#> Median :2.00 Median : 4675.0
#> Mean :1.53 Mean : 5952.2
#> 3rd Qu.:2.00 3rd Qu.: 9370.5
#> Max. :3.00 Max. :27094.7
#>