Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\28545117
.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117 PLoS+One
2017 ; 12
(5
): e0177682
Nephropedia Template TP
gab.com Text
Twit Text FOAVip
Twit Text #
English Wikipedia
On tests of treatment-covariate interactions: An illustration of appropriate
power and sample size calculations
#MMPMID28545117
Shieh G
PLoS One
2017[]; 12
(5
): e0177682
PMID28545117
show ga
The appraisals of treatment-covariate interaction have theoretical and
substantial implications in all scientific fields. Methodologically, the
detection of interaction between categorical treatment levels and continuous
covariate variables is analogous to the homogeneity of regression slopes test in
the context of ANCOVA. A fundamental assumption of ANCOVA is that the regression
slopes associating the response variable with the covariate variable are presumed
constant across treatment groups. The validity of homogeneous regression slopes
accordingly is the most essential concern in traditional ANCOVA and inevitably
determines the practical usefulness of research findings. In view of the limited
results in current literature, this article aims to present power and sample size
procedures for tests of heterogeneity between two regression slopes with
particular emphasis on the stochastic feature of covariate variables. Theoretical
implications and numerical investigations are presented to explicate the utility
and advantage for accommodating covariate properties. The exact approach has the
distinct feature of accommodating the full distributional properties of normal
covariates whereas the simplified approximate methods only utilize the partial
information of covariate variances. According to the overall accuracy and
robustness, the exact approach is recommended over the approximate methods as a
reliable tool in practical applications. The suggested power and sample size
calculations can be implemented with the supplemental SAS and R programs.