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Bring more data!—a good advice? : removing separation in logistic regression by increasing sample size
ID
Šinkovec, Hana
(
Avtor
),
ID
Geroldinger, Angelika
(
Avtor
),
ID
Heinze, Georg
(
Avtor
)
PDF - Predstavitvena datoteka,
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MD5: 479F8B3D9EBE1B05FB9B3629BCBAA68E
URL - Izvorni URL, za dostop obiščite
https://www.mdpi.com/1660-4601/16/23/4658
Galerija slik
Izvleček
The parameters of logistic regression models are usually obtained by the method of maximum likelihood (ML). However, in analyses of small data sets or data sets with unbalanced outcomes or exposures, ML parameter estimates may not exist. This situation has been termed ‘separation’ as the two outcome groups are separated by the values of a covariate or a linear combination of covariates. To overcome the problem of non-existing ML parameter estimates, applying Firth’s correction (FC) was proposed. In practice, however, a principal investigator might be advised to ‘bring more data’ in order to solve a separation issue. We illustrate the problem by means of examples from colorectal cancer screening and ornithology. It is unclear if such an increasing sample size (ISS) strategy that keeps sampling new observations until separation is removed improves estimation compared to applying FC to the original data set. We performed an extensive simulation study where the main focus was to estimate the cost-adjusted relative efficiency of ML combined with ISS compared to FC. FC yielded reasonably small root mean squared errors and proved to be the more efficient estimator. Given our findings, we propose not to adapt the sample size when separation is encountered but to use FC as the default method of analysis whenever the number of observations or outcome events is critically low.
Jezik:
Angleški jezik
Ključne besede:
maximum likelihood estimation
,
logistic regression
,
Firth’s correction
,
separation
,
penalized likelihood
,
bias
Vrsta gradiva:
Članek v reviji
Tipologija:
1.01 - Izvirni znanstveni članek
Organizacija:
BF - Biotehniška fakulteta
Status publikacije:
Objavljeno
Različica publikacije:
Objavljena publikacija
Leto izida:
2019
Št. strani:
12 str.
Številčenje:
Vol. 16, no. 23
PID:
20.500.12556/RUL-153007
UDK:
61
ISSN pri članku:
1660-4601
DOI:
10.3390/ijerph16234658
COBISS.SI-ID:
177404163
Datum objave v RUL:
14.12.2023
Število ogledov:
820
Število prenosov:
22
Metapodatki:
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Objavi na:
Gradivo je del revije
Naslov:
International journal of environmental research and public health
Skrajšan naslov:
Int. j. environ. res. public health
Založnik:
MDPI
ISSN:
1660-4601
COBISS.SI-ID:
1818965
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