Linear regression analysis with missing observations among the independent variables in animal breeding

被引：0

作者：

Kayaalp, GT ^{[1
]}

机构：

[1] Univ Gaziosmanpasa, Fac Agr, Dept Anim Sci, Tokat, Turkey

来源：

TURKISH JOURNAL OF VETERINARY & ANIMAL SCIENCES | 1999年 / 23卷 / 02期

关键词：

regression analysis; least square estimation; missing observations;

D O I：

暂无

中图分类号：

S85 [动物医学（兽医学）];

学科分类号：

0906 ;

摘要：

In animal breeding, when there is a relationship between the dependent (Y) and independent (X) variables. regression analysis is applied. But when one of the variables has one or more missing observations regression analysis cannot be applied. This paper illustrates and discusses a regression analysis in which the independent variable (X) has a missing observation.

引用

页码：149 / 151

页数：3

共 50 条

[41] INTERIOR ANALYSIS OF THE OBSERVATIONS IN MULTIPLE LINEAR-REGRESSION
MONTGOMERY, DC
MARTIN, EW
PECK, EA
[J]. JOURNAL OF QUALITY TECHNOLOGY, 1980, 12 (03) : 165 - 173
[42] Multivariate linear regression model with elliptically contoured distributed errors and monotone missing dependent variables
Batsidis, A.
Zografos, K.
[J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2008, 37 (03) : 349 - 372
[43] Semiparametric Analysis of Isotonic Errors-in-Variables Regression Models with Missing Response
Sun, Zhimeng
Zhang, Zhongzhan
Du, Jiang
[J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2012, 41 (11) : 2034 - 2060
[44] DATA ENVELOPMENT ANALYSIS WITH MISSING DATA: A MULTIPLE LINEAR REGRESSION ANALYSIS APPROACH
Chen, Ya
Li, Yongjun
Wu, Huaqing
Liang, Liang
[J]. INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING, 2014, 13 (01) : 137 - 153
[45] FUZZY LINEAR-REGRESSION ANALYSIS OF FUZZY VALUED VARIABLES
WANG, ZY
LI, SM
[J]. FUZZY SETS AND SYSTEMS, 1990, 36 (01) : 125 - 136
[46] STATISTICAL ANALYSIS OF A LINEAR REGRESSION MODEL WITH RESTRICTIONS AND SUPERFLUOUS VARIABLES
Li, Wenming
Tian, Yongge
Yuan, Ruixia
[J]. JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION, 2023, 19 (05) : 3107 - 3127
[47] MODEL ESTIMATION WHEN OBSERVATIONS ARE NOT INDEPENDENT - APPLICATION OF LIANG AND ZEGER METHODOLOGY TO LINEAR AND LOGISTIC-REGRESSION ANALYSIS
BYE, BV
RILEY, GF
[J]. SOCIOLOGICAL METHODS & RESEARCH, 1989, 17 (04) : 353 - 375
[48] A study over the Formulation of the Parameters 5 or Less Independent Variables of Multiple Linear Regression
Korkmaz, Mehmet
[J]. JOURNAL OF FUNCTION SPACES, 2019, 2019
[49] Methods for the Analysis of Explanatory Linear Regression Models with Missing Data Not at Random
José Blas Navarro Pastor
[J]. Quality and Quantity, 2003, 37 (4) : 363 - 376
[50] THE ITERATIVE TRANSFORMATION OF INDEPENDENT VARIABLES IN REGRESSION-ANALYSIS OF GEOLOGICAL DATA
ZHANG, Q
[J]. SCIENTIA GEOLOGICA SINICA, 1986, (04): : 401 - 410

← 1 2 3 4 5 →