Data
plasma_retinol

plasma_retinol

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Author: Source: Unknown - Date unknown Please cite: Determinants of Plasma Retinol and Beta-Carotene Levels Summary: Observational studies have suggested that low dietary intake or low plasma concentrations of retinol, beta-carotene, or other carotenoids might be associated with increased risk of developing certain types of cancer. However, relatively few studies have investigated the determinants of plasma concentrations of these micronutrients. We designed a cross-sectional study to investigate the relationship between personal characteristics and dietary factors, and plasma concentrations of retinol, beta-carotene and other carotenoids. Study subjects (N = 315) were patients who had an elective surgical procedure during a three-year period to biopsy or remove a lesion of the lung, colon, breast, skin, ovary or uterus that was found to be non-cancerous. We display the data for only two of the analytes. Plasma concentrations of the micronutrients varied widely from subject to subject. While plasma retinol levels varied by age and sex, the only dietary predictor was alcohol consumption (R^2 = .38). Plasma beta-carotene levels were log-transformed prior to the analyses due to severe asymmetry of the residuals on the original scale. For log beta-carotene, dietary intake, regular use of vitamins, and intake of fiber were associated with higher plasma concentrations, while Quetelet Index (defined as weight/height^2 in the units kg/m^2) and cholesterol intake were associated with lower plasma levels, adjusting for the other factors (R^2 = .50). There was one extremely high leverage point in alcohol consumption that was deleted prior to the analyses. Plasma concentrations of retinol and beta-carotene were not correlated. We conclude that there is wide variability in plasma concentrations of these micronutrients in humans, and that much of this variability is associated with dietary habits and personal characteristics. A better understanding of the physiological relationship between some personal characteristics and plasma concentrations of these micronutrients will require further study. Authorization: Contact Authors Reference: These data have not been published yet but a related reference is Nierenberg DW, Stukel TA, Baron JA, Dain BJ, Greenberg ER. Determinants of plasma levels of beta-carotene and retinol. American Journal of Epidemiology 1989;130:511-521. Description: This datafile contains 315 observations on 14 variables. This data set can be used to demonstrate multiple regression, transformations, categorical variables, outliers, pooled tests of significance and model building strategies. Variable Names in order from left to right: AGE: Age (years) SEX: Sex (1=Male, 2=Female). SMOKSTAT: Smoking status (1=Never, 2=Former, 3=Current Smoker) QUETELET: Quetelet (weight/(height^2)) VITUSE: Vitamin Use (1=Yes, fairly often, 2=Yes, not often, 3=No) CALORIES: Number of calories consumed per day. FAT: Grams of fat consumed per day. FIBER: Grams of fiber consumed per day. ALCOHOL: Number of alcoholic drinks consumed per week. CHOLESTEROL: Cholesterol consumed (mg per day). BETADIET: Dietary beta-carotene consumed (mcg per day). RETDIET: Dietary retinol consumed (mcg per day) BETAPLASMA: Plasma beta-carotene (ng/ml) RETPLASMA: Plasma Retinol (ng/ml) Therese Stukel Dartmouth Hitchcock Medical Center One Medical Center Dr. Lebanon, NH 03756 e-mail: stukel@dartmouth.edu Information about the dataset CLASSTYPE: numeric CLASSINDEX: none specific

14 features

RETPLASMA (target)numeric257 unique values
0 missing
AGEnumeric60 unique values
0 missing
SEXnominal2 unique values
0 missing
SMOKSTATnominal3 unique values
0 missing
QUETELETnumeric258 unique values
0 missing
VITUSEnominal3 unique values
0 missing
CALORIESnumeric311 unique values
0 missing
FATnumeric275 unique values
0 missing
FIBERnumeric157 unique values
0 missing
ALCOHOLnumeric71 unique values
0 missing
CHOLESTEROLnumeric304 unique values
0 missing
BETADIETnumeric302 unique values
0 missing
RETDIETnumeric278 unique values
0 missing
BETAPLASMAnumeric212 unique values
0 missing
Show all 14 features

107 properties

NumberOfInstances
315
Number of instances (rows) of the dataset.
NumberOfFeatures
14
Number of attributes (columns) of the dataset.
NumberOfClasses
0
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
11
Number of numeric attributes.
NumberOfSymbolicFeatures
3
Number of nominal attributes.
MeanSkewnessOfNumericAtts
2.9
Mean skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
12.32
First quartile of standard deviation of attributes of the numeric type.
REPTreeDepth2AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NErrRate
Error rate achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
kNN1NAUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
J48.001.Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanStdDevOfNumericAtts
303.59
Mean standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
REPTreeDepth2ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NKappa
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
kNN1NErrRate
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
MinAttributeEntropy
Minimal entropy among attributes.
Quartile2KurtosisOfNumericAtts
3.47
Second quartile (Median) of kurtosis among attributes of the numeric type.
REPTreeDepth2Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
ClassEntropy
Entropy of the target attribute values.
kNN1NKappa
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassSize
Number of instances belonging to the most frequent class.
MinKurtosisOfNumericAtts
-0.87
Minimum kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
189.89
Second quartile (Median) of means among attributes of the numeric type.
REPTreeDepth3AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpAUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxAttributeEntropy
Maximum entropy among attributes.
MinMeansOfNumericAtts
3.28
Minimum of means among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
REPTreeDepth3ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpErrRate
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxKurtosisOfNumericAtts
221.33
Maximum kurtosis among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
1.48
Second quartile (Median) of skewness among attributes of the numeric type.
REPTreeDepth3Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpKappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxMeansOfNumericAtts
2185.6
Maximum of means among attributes of the numeric type.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
PercentageOfBinaryFeatures
7.14
Percentage of binary attributes.
Quartile2StdDevOfNumericAtts
131.99
Second quartile (Median) of standard deviation of attributes of the numeric type.
RandomTreeDepth1AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Dimensionality
0.04
Number of attributes divided by the number of instances.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MinSkewnessOfNumericAtts
0.3
Minimum skewness among attributes of the numeric type.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
RandomTreeDepth1ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MaxNominalAttDistinctValues
3
The maximum number of distinct values among attributes of the nominal type.
MinStdDevOfNumericAtts
5.33
Minimum standard deviation of attributes of the numeric type.
PercentageOfMissingValues
0
Percentage of missing values.
Quartile3KurtosisOfNumericAtts
17.21
Third quartile of kurtosis among attributes of the numeric type.
AutoCorrelation
-196.47
Average class difference between consecutive instances.
RandomTreeDepth1Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
J48.00001.AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxSkewnessOfNumericAtts
13.82
Maximum skewness among attributes of the numeric type.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
PercentageOfNumericFeatures
78.57
Percentage of numeric attributes.
Quartile3MeansOfNumericAtts
832.71
Third quartile of means among attributes of the numeric type.
CfsSubsetEval_DecisionStumpAUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
RandomTreeDepth2AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxStdDevOfNumericAtts
1473.89
Maximum standard deviation of attributes of the numeric type.
MinorityClassSize
Number of instances belonging to the least frequent class.
PercentageOfSymbolicFeatures
21.43
Percentage of nominal attributes.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
CfsSubsetEval_DecisionStumpErrRate
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
RandomTreeDepth2ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MeanAttributeEntropy
Average entropy of the attributes.
NaiveBayesAUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile3SkewnessOfNumericAtts
3.56
Third quartile of skewness among attributes of the numeric type.
CfsSubsetEval_DecisionStumpKappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
RandomTreeDepth2Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.0001.AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanKurtosisOfNumericAtts
27.39
Mean kurtosis among attributes of the numeric type.
NaiveBayesErrRate
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1KurtosisOfNumericAtts
2.02
First quartile of kurtosis among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
589.29
Third quartile of standard deviation of attributes of the numeric type.
CfsSubsetEval_NaiveBayesAUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
RandomTreeDepth3AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMeansOfNumericAtts
547.23
Mean of means among attributes of the numeric type.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
NaiveBayesKappa
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1MeansOfNumericAtts
26.16
First quartile of means among attributes of the numeric type.
REPTreeDepth1AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesErrRate
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
RandomTreeDepth3ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
NumberOfBinaryFeatures
1
Number of binary attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
REPTreeDepth1ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesKappa
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
RandomTreeDepth3Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.001.AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanNominalAttDistinctValues
2.67
Average number of distinct values among the attributes of the nominal type.
Quartile1SkewnessOfNumericAtts
1.15
First quartile of skewness among attributes of the numeric type.
REPTreeDepth1Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_kNN1NAUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
StdvNominalAttDistinctValues
0.58
Standard deviation of the number of distinct values among attributes of the nominal type.
J48.001.ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
Show all 107 properties

13 tasks

Supervised Regression on plasma_retinol
15 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: RETPLASMA
Supervised Regression on plasma_retinol
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: RETPLASMA
Clustering on plasma_retinol
0 runs - estimation_procedure: 50 times Clustering
Clustering on plasma_retinol
0 runs - estimation_procedure: 50 times Clustering
Clustering on plasma_retinol
0 runs - estimation_procedure: 50 times Clustering
Clustering on plasma_retinol
0 runs - estimation_procedure: 50 times Clustering
Clustering on plasma_retinol
0 runs - estimation_procedure: 50 times Clustering
Clustering on plasma_retinol
0 runs
Clustering on plasma_retinol
0 runs - estimation_procedure: 50 times Clustering
Clustering on plasma_retinol
0 runs - estimation_procedure: 50 times Clustering
Clustering on plasma_retinol
0 runs - estimation_procedure: 50 times Clustering
Clustering on plasma_retinol
0 runs - estimation_procedure: 50 times Clustering
Clustering on plasma_retinol
0 runs - estimation_procedure: 50 times Clustering
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