Subject-matter considerations in assessing the fit of a linear regression model

Michele Callisaya; Au Bich Thuy; Leigh Blizzard; Michael D Schmidt; Jennifer Louise McGinley; Velandai Srikanth

Subject-matter considerations in assessing the fit of a linear regression model

Michele Callisaya, Au Bich Thuy, Leigh Blizzard, Michael D Schmidt, Jennifer Louise McGinley, Velandai Srikanth

Research output: Contribution to journal › Article › Research › peer-review

Abstract

Gait disorders become increasingly common with age, with the prevalence of abnormal gain reported to be as high as 35 in adults over 70 years.

Original language	English
Pages (from-to)	35 - 37
Number of pages	3
Journal	Australasian Epidemiologist
Volume	14
Issue number	2
Publication status	Published - 2007
Externally published	Yes

Cite this

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title = "Subject-matter considerations in assessing the fit of a linear regression model",

abstract = "Gait disorders become increasingly common with age, with the prevalence of abnormal gain reported to be as high as 35 in adults over 70 years.",

author = "Michele Callisaya and Thuy, \{Au Bich\} and Leigh Blizzard and Schmidt, \{Michael D\} and McGinley, \{Jennifer Louise\} and Velandai Srikanth",

year = "2007",

language = "English",

volume = "14",

pages = "35 -- 37",

journal = "Australasian Epidemiologist",

issn = "1327-8835",

publisher = "Australasian Epidemiological Association",

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AU - Callisaya, Michele

AU - Thuy, Au Bich

AU - Blizzard, Leigh

AU - Schmidt, Michael D

AU - McGinley, Jennifer Louise

AU - Srikanth, Velandai

PY - 2007

Y1 - 2007

N2 - Gait disorders become increasingly common with age, with the prevalence of abnormal gain reported to be as high as 35 in adults over 70 years.

AB - Gait disorders become increasingly common with age, with the prevalence of abnormal gain reported to be as high as 35 in adults over 70 years.

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M3 - Article

SN - 1327-8835

VL - 14

SP - 35

EP - 37

JO - Australasian Epidemiologist

JF - Australasian Epidemiologist

IS - 2

ER -

Subject-matter considerations in assessing the fit of a linear regression model

Abstract

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