Abstract
Correlation coefficient estimates are often attenuated for truncated samples in the sense that the estimates are biased towards zero. Motivated by real data collected in South Sudan, we consider correlation coefficient estimation with singly truncated bivariate data. By considering a linear regression model in which a truncated variable is used as an explanatory variable, a consistent estimator for the regression slope can be obtained from the ordinary least squares method. A consistent estimator of the correlation coefficient is then obtained by multiplying the regression slope estimator by the variance ratio of the two variables. Results from two limited simulation studies confirm the validity and robustness of the proposed method. The proposed method is applied to the South Sudanese children's anthropometric and nutritional data collected by World Vision.
| Original language | English |
|---|---|
| Pages (from-to) | 1977-1988 |
| Number of pages | 12 |
| Journal | Statistics in Medicine |
| Volume | 36 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - 2017 May 30 |
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All Science Journal Classification (ASJC) codes
- Epidemiology
- Statistics and Probability
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Correlation estimation with singly truncated bivariate data. / Im, Jongho; Ahn, Eunyong; Beck, Namseon; Kim, Jae Kwang; Park, Taesung.
In: Statistics in Medicine, Vol. 36, No. 12, 30.05.2017, p. 1977-1988.Research output: Contribution to journal › Article
TY - JOUR
T1 - Correlation estimation with singly truncated bivariate data
AU - Im, Jongho
AU - Ahn, Eunyong
AU - Beck, Namseon
AU - Kim, Jae Kwang
AU - Park, Taesung
PY - 2017/5/30
Y1 - 2017/5/30
N2 - Correlation coefficient estimates are often attenuated for truncated samples in the sense that the estimates are biased towards zero. Motivated by real data collected in South Sudan, we consider correlation coefficient estimation with singly truncated bivariate data. By considering a linear regression model in which a truncated variable is used as an explanatory variable, a consistent estimator for the regression slope can be obtained from the ordinary least squares method. A consistent estimator of the correlation coefficient is then obtained by multiplying the regression slope estimator by the variance ratio of the two variables. Results from two limited simulation studies confirm the validity and robustness of the proposed method. The proposed method is applied to the South Sudanese children's anthropometric and nutritional data collected by World Vision.
AB - Correlation coefficient estimates are often attenuated for truncated samples in the sense that the estimates are biased towards zero. Motivated by real data collected in South Sudan, we consider correlation coefficient estimation with singly truncated bivariate data. By considering a linear regression model in which a truncated variable is used as an explanatory variable, a consistent estimator for the regression slope can be obtained from the ordinary least squares method. A consistent estimator of the correlation coefficient is then obtained by multiplying the regression slope estimator by the variance ratio of the two variables. Results from two limited simulation studies confirm the validity and robustness of the proposed method. The proposed method is applied to the South Sudanese children's anthropometric and nutritional data collected by World Vision.
UR - http://www.scopus.com/inward/record.url?scp=85013909046&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85013909046&partnerID=8YFLogxK
U2 - 10.1002/sim.7267
DO - 10.1002/sim.7267
M3 - Article
C2 - 28239899
AN - SCOPUS:85013909046
VL - 36
SP - 1977
EP - 1988
JO - Statistics in Medicine
JF - Statistics in Medicine
SN - 0277-6715
IS - 12
ER -