This paper presents a command, glst, for trend estimation across different exposure levels for either single or multiple summarized case–control, incidence-rate, and cumulative incidence data. This approach is based on constructing an approximate covariance estimate for the log relative risks and estimating a corrected linear trend using generalized least squares. For trend analysis of multiple studies, glst can estimate fixed- and random-effects metaregression models.

Orsini, N., Bellocco, R., Greenland, S. (2006). Generalized least squares for trend estimation of summarized dose-response data. THE STATA JOURNAL, 6(1), 40-57 [10.1177/1536867x0600600103].

Generalized least squares for trend estimation of summarized dose-response data

BELLOCCO, RINO;
2006

Abstract

This paper presents a command, glst, for trend estimation across different exposure levels for either single or multiple summarized case–control, incidence-rate, and cumulative incidence data. This approach is based on constructing an approximate covariance estimate for the log relative risks and estimating a corrected linear trend using generalized least squares. For trend analysis of multiple studies, glst can estimate fixed- and random-effects metaregression models.
Articolo in rivista - Articolo scientifico
Stata, Meta-analysis, Dose-response
English
2006
6
1
40
57
none
Orsini, N., Bellocco, R., Greenland, S. (2006). Generalized least squares for trend estimation of summarized dose-response data. THE STATA JOURNAL, 6(1), 40-57 [10.1177/1536867x0600600103].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/26811
Citazioni
  • Scopus 1100
  • ???jsp.display-item.citation.isi??? 1082
Social impact