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Items: 1 to 20 of 93

1.

Log-transformation and its implications for data analysis.

Feng C, Wang H, Lu N, Chen T, He H, Lu Y, Tu XM.

Shanghai Arch Psychiatry. 2014 Apr;26(2):105-9. doi: 10.3969/j.issn.1002-0829.2014.02.009.

2.

Sample size calculations based on a difference in medians for positively skewed outcomes in health care studies.

O'Keeffe AG, Ambler G, Barber JA.

BMC Med Res Methodol. 2017 Dec 2;17(1):157. doi: 10.1186/s12874-017-0426-1.

3.

Log transformation: application and interpretation in biomedical research.

Feng C, Wang H, Lu N, Tu XM.

Stat Med. 2013 Jan 30;32(2):230-9. doi: 10.1002/sim.5486. Epub 2012 Jul 16.

PMID:
22806695
4.

A comparison of methods to handle skew distributed cost variables in the analysis of the resource consumption in schizophrenia treatment.

Kilian R, Matschinger H, Löeffler W, Roick C, Angermeyer MC.

J Ment Health Policy Econ. 2002 Mar;5(1):21-31.

PMID:
12529567
5.

Generalized modeling approaches to risk adjustment of skewed outcomes data.

Manning WG, Basu A, Mullahy J.

J Health Econ. 2005 May;24(3):465-88.

PMID:
15811539
6.

Dealing with skewed data: an example using asthma-related costs of medicaid clients.

Rascati KL, Smith MJ, Neilands T.

Clin Ther. 2001 Mar;23(3):481-98.

PMID:
11318082
7.

Detecting skewness from summary information.

Altman DG, Bland JM.

BMJ. 1996 Nov 9;313(7066):1200.

8.

A simple method for optimising transformation of non-parametric data: an illustration by reference to cortisol assays.

Clark JE, Osborne JW, Gallagher P, Watson S.

Hum Psychopharmacol. 2016 Jul;31(4):259-67. doi: 10.1002/hup.2528. Epub 2016 May 27.

PMID:
27230811
9.

Normative references of heart rate variability and salivary alpha-amylase in a healthy young male population.

Kobayashi H, Park BJ, Miyazaki Y.

J Physiol Anthropol. 2012 Apr 20;31:9. doi: 10.1186/1880-6805-31-9.

10.

Optimizing transformations for automated, high throughput analysis of flow cytometry data.

Finak G, Perez JM, Weng A, Gottardo R.

BMC Bioinformatics. 2010 Nov 4;11:546. doi: 10.1186/1471-2105-11-546.

11.

A proposed method of logarithmic transformation of optical coherence tomography data for use in clinical research.

Ferris FL 3rd, Miller KM, Glassman AR, Beck RW; Diabetic Retinopathy Clinical Research Network.

Ophthalmology. 2010 Aug;117(8):1512-6. doi: 10.1016/j.ophtha.2009.12.014. Epub 2010 Apr 3.

12.

Methods for comparison of cost data.

Zhou XH, Melfi CA, Hui SL.

Ann Intern Med. 1997 Oct 15;127(8 Pt 2):752-6.

PMID:
9382393
13.
14.

A Bayesian generalized random regression model for estimating heritability using overdispersed count data.

Mair C, Stear M, Johnson P, Denwood M, Jimenez de Cisneros JP, Stefan T, Matthews L.

Genet Sel Evol. 2015 Jun 20;47:51. doi: 10.1186/s12711-015-0125-5.

15.

The lognormal distribution, environmental data, and radiological monitoring.

Blackwood LG.

Environ Monit Assess. 1992 Jun;21(3):193-210. doi: 10.1007/BF00399687.

PMID:
24234486
16.

The logarithmic transformation and the geometric mean in reporting experimental IgE results: what are they and when and why to use them?

Olivier J, Johnson WD, Marshall GD.

Ann Allergy Asthma Immunol. 2008 Apr;100(4):333-7. doi: 10.1016/S1081-1206(10)60595-9. Erratum in: Ann Allergy Asthma Immunol. 2008 Jun;100(6):625-6.

PMID:
18450118
17.

A random effects meta-analysis model with Box-Cox transformation.

Yamaguchi Y, Maruo K, Partlett C, Riley RD.

BMC Med Res Methodol. 2017 Jul 19;17(1):109. doi: 10.1186/s12874-017-0376-7.

18.

Transformations of covariates for longitudinal data.

Thompson WK, Xie M, White HR.

Biostatistics. 2003 Jul;4(3):353-64.

PMID:
12925503
19.

Analyzing family data: A GEE approach for substance use researchers.

Homish GG, Edwards EP, Eiden RD, Leonard KE.

Addict Behav. 2010 Jun;35(6):558-63. doi: 10.1016/j.addbeh.2010.01.002. Epub 2010 Feb 1.

20.

To transform or not transform skewed data for psychometric analysis: that is the question!

Norris AE, Aroian KJ.

Nurs Res. 2004 Jan-Feb;53(1):67-71. Review.

PMID:
14726780

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