TY - JOUR
T1 - Trend analysis with response incompatible formats and measurement error
AU - Kowalski, J.
AU - Tu, X. M.
N1 - Funding Information:
We thank Editor Dr. Kanji and one anonymous reviewer for helpful comments that led to an improved presentation. This research was supported in part by an NIH/ NIAID award AI 51186 (Kowalski) and an NIH/NIAID award AI 36627 (Tu).
PY - 2003/8
Y1 - 2003/8
N2 - The increasing popularity of longitudinal studies, along with the rapid advances in science and technology, has created a potential incompatibility between data formats, which leads to an inference problem when applying conventional statistical methods. This inference problem is further compounded by measurement error, since incompatible data format often arise in the context of measuring latent constructs. Without a systematic study of the impact of scale differences, ad-hoc approaches generally lead to inconsistent estimates and thus, invalid statistical inferences. In this paper, we examine the asymptotic properties and identify conditions that guarantee consistent estimation within the context of a trend analysis with response incompatible formats and measurement error. For model estimation, we introduce two competing methods that use a generalized estimating equation approach to provide inferences for the parameters of interest, and highlight the relative strengths of each method. The approach is illustrated by data obtained from a multi-centre AIDS cohort study (MACS), where a trend analysis of an immunologic marker of HIV infection is of interest.
AB - The increasing popularity of longitudinal studies, along with the rapid advances in science and technology, has created a potential incompatibility between data formats, which leads to an inference problem when applying conventional statistical methods. This inference problem is further compounded by measurement error, since incompatible data format often arise in the context of measuring latent constructs. Without a systematic study of the impact of scale differences, ad-hoc approaches generally lead to inconsistent estimates and thus, invalid statistical inferences. In this paper, we examine the asymptotic properties and identify conditions that guarantee consistent estimation within the context of a trend analysis with response incompatible formats and measurement error. For model estimation, we introduce two competing methods that use a generalized estimating equation approach to provide inferences for the parameters of interest, and highlight the relative strengths of each method. The approach is illustrated by data obtained from a multi-centre AIDS cohort study (MACS), where a trend analysis of an immunologic marker of HIV infection is of interest.
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U2 - 10.1080/0266476032000076038
DO - 10.1080/0266476032000076038
M3 - Article
AN - SCOPUS:0041845250
SN - 0266-4763
VL - 30
SP - 751
EP - 770
JO - Journal of Applied Statistics
JF - Journal of Applied Statistics
IS - 7
ER -