STATISTICS :
DATA :
MISTAKES :
ERRORS :
FALSIFICATION :
FABRICATION:
Falsification Mistakes and Errors in Statistical Data Found in Publications
.
.
Falsification Mistakes and Errors in Statistical Data Found in Publications
Search Strategy
(statistical OR data OR statistics) AND (books OR articles OR publications OR published) AND (errors OR mistakes OR false OR falsified OR falsifications OR distortions OR corruption OR fabrications OR misrepresentations OR disinformation)
Van Oosterhout, Cock, William F. Hutchinson,
Derek PM Wills, and Peter Shipley.
“MICRO‐CHECKER: software for identifying and correcting
genotyping errors in microsatellite data.”
Molecular Ecology Notes 4, no. 3 (2004): 535-538.
*
Jacob, Herbert.
Using published data: Errors and remedies.
Vol. 42. Sage, 1984.
*
Simmons, Joseph P., Leif D. Nelson, and Uri Simonsohn.
“False-positive psychology undisclosed flexibility
in data collection and analysis allows presenting anything as significant.”
Psychological science (2011): 0956797611417632.
*
Petersen, Mitchell A.
“Estimating standard errors in finance panel data sets:
Comparing approaches.”
Review of financial studies 22, no. 1 (2009): 435-480.
*
Ioannidis, John PA.
“Why most published research findings are false.”
PLoS Med 2, no. 8 (2005): e124.
*
Rogers, William.
“Regression standard errors in clustered samples.”
Stata technical bulletin 3, no. 13 (1994).
*
Sippl, Manfred J.
“Recognition of errors in three‐dimensional structures of proteins.”
Proteins: Structure, Function, and Bioinformatics
17, no. 4 (1993): 355-362.
*
Spathis, Charalambos T.
“Detecting false financial statements using published data:
some evidence from Greece.”
Managerial Auditing Journal 17, no. 4 (2002): 179-191.
*
Genovese, Christopher R., Nicole A. Lazar, and Thomas Nichols.
“Thresholding of statistical maps in functional neuroimaging
using the false discovery rate.”
Neuroimage 15, no. 4 (2002): 870-878.
*
Andersen, Bjørn.
Methodological errors in medical research: an incomplete catalogue.
Blackwell Scientific, 1990.
*
Lang, Tom.
“Twenty statistical errors even you can find in biomedical research articles.”
(2004): 361-370.
*
Akritas, Michael G., and Matthew A. Bershady.
“Linear regression for astronomical data with measurement errors
and intrinsic scatter.”
arXiv preprint astro-ph/9605002 (1996).
*
Benjamini, Yoav, and Yosef Hochberg.
“On the adaptive control of the false discovery rate
in multiple testing with independent statistics.”
Journal of educational and Behavioral Statistics
25, no. 1 (2000): 60-83.
*
Flynn, Elizabeth A., Kenneth N. Barker, Ginette A. Pepper,
David W. Bates, and Robert L. Mikeal.
“Comparison of methods for detecting medication errors
in 36 hospitals and skilled-nursing facilities.”
American Journal of Health-System Pharmacy
59, no. 5 (2002): 436-446.
*
Bennett, Craig M., George L. Wolford, and Michael B. Miller.
“The principled control of false positives in neuroimaging.”
Social cognitive and affective neuroscience 4, no. 4 (2009): 417-422.
*
Griliches, Zvi, and Jerry A. Hausman.
“Errors in variables in panel data.”
Journal of econometrics 31, no. 1 (1986): 93-118.
*
Swenson, Sean, and John Wahr.
“Post‐processing removal of correlated errors in GRACE data.”
Geophysical Research Letters 33, no. 8 (2006).
*
Williams, JOHN L., CHRISTOPHER A. Hathaway, KAIA L. Kloster,
and BENJAMIN H. Layne.
“Low power, type II errors, and other statistical problems
in recent cardiovascular research.”
The American journal of physiology 273, no. 1 Pt 2 (1997): H487-93.
*
Henson, Robin K., and J. Kyle Roberts.
“Use of exploratory factor analysis in published research
common errors and some comment on improved practice.”
Educational and Psychological measurement 66, no. 3 (2006): 393-416.
*
Barry, Benjamin Austin.
Errors in practical measurement in science, engineering, and technology.
John Wiley & Sons Inc, 1978.
*.
Lincoln, Stephen E., and Eric S. Lander.
“Systematic detection of errors in genetic linkage data.”
Genomics 14, no. 3 (1992): 604-610.
*
Broadhurst, David I., and Douglas B. Kell.
“Statistical strategies for avoiding false discoveries
in metabolomics and related experiments.”
Metabolomics 2, no. 4 (2006): 171-196.
*
Fromkin, Victoria.
Errors in linguistic performance: Slips of the tongue, ear, pen, and hand.
Academic Press, 1980.
*
Pierce, Donald A., Daniel O. Stram, and Michael Vaeth.
“Allowing for random errors in radiation dose estimates
for the atomic bomb survivor data.”
Radiation research 123, no. 3 (1990): 275-284.
*
Bentler, Peter M.
“Corrections to test statistics and standard errors
in covariance structure analysis.”
Latent Variables Analysis: Applications for (1994).
*
Benjamini, Yoav, Dan Drai, Greg Elmer, Neri Kafkafi, and Ilan Golani.
“Controlling the false discovery rate in behavior genetics research.”
Behavioural brain research 125, no. 1 (2001): 279-284.
*
Schmidt, Frank L., and John E. Hunter.
“Eight common but false objections to the discontinuation
of significance testing in the analysis of research data.” (1997): 37-63.
*
Laws, Rules, and Regional Economic Outlook.
“Corruption and the rate of temptation: do low wages
in the civil service cause corruption?.” (1997).
Van Rijckeghem, Caroline and Weder, Beatrice,
Corruption and the Rate of Temptation:
Do Low Wages in the Civil Service Cause Corruption?
(June 1997).
IMF Working Paper, Vol. , pp. 1-56, 1997.
Available at SSRN: http://ssrn.com/abstract=882353
*
White, SUSAN J.
“Statistical errors in papers in the British Journal of Psychiatry.”
The British Journal of Psychiatry 135, no. 4 (1979): 336-342.
*
Deszcz-Pan, Maryla, David V. Fitterman, and Victor F. Labson.
“Reduction of inversion errors in helicopter EM data
using auxiliary information.”
Exploration Geophysics 29, no. 1/2 (1998): 142-146.
*
Sekas, Gail, and William R. Hutson.
“Misrepresentation of academic accomplishments by applicants
for gastroenterology fellowships.”
Annals of internal medicine 123, no. 1 (1995): 38-41.
*
Sims, David W., David Righton, and Jonathan W. Pitchford.
“Minimizing errors in identifying Lévy flight behaviour of organisms.”
Journal of Animal Ecology 76, no. 2 (2007): 222-229.
*
Phillips, Jerry, Sammie Beam, Allen Brinker, Carol Holquist,
Peter Honig, Laureen Y. Lee, and Carol Pamer.
“Retrospective analysis of mortalities associated with medication errors.”
American Journal of Health-System Pharmacy
58, no. 19 (2001): 1835-1841.
*
Dawes, Robyn M.
“Statistical criteria for establishing a truly false consensus effect.”
Journal of Experimental Social Psychology 25, no. 1 (1989): 1-17.
*
Liu, David, Henry M. Wellman, Twila Tardif, and Mark A. Sabbagh.
“Theory of mind development in Chinese children:
a meta-analysis of false-belief understanding
across cultures and languages.”
Developmental psychology 44, no. 2 (2008): 523.
*
Laird, Angela R., P. Mickle Fox, Cathy J. Price, David C. Glahn,
Angela M. Uecker, Jack L. Lancaster, Peter E. Turkeltaub,
Peter Kochunov, and Peter T. Fox.
“ALE meta‐analysis: Controlling the false discovery rate and
performing statistical contrasts.”
Human brain mapping 25, no. 1 (2005): 155-164.
*
Ioannidis, John PA.
“Genetic associations: false or true?.”
Trends in molecular medicine 9, no. 4 (2003): 135-138.
*
Chelton, Dudley B.
“Effects of sampling errors in statistical estimation.”
Deep Sea Research Part A.
Oceanographic Research Papers 30, no. 10 (1983): 1083-1103.
*
Carrier, Norman, and John Hobcraft.
“Demographic estimation for developing societies.
A manual of techniques For the detection and reduction
of errors in demographic data.”
Demographic estimation for developing societies.
A manual of techniques For the detection and reduction of
errors in demographic data. (1971).
*
Choi, Hyungwon, and Alexey I. Nesvizhskii.
“False discovery rates and related statistical concepts in mass
spectrometry-based proteomics.”
Journal of proteome research 7, no. 01 (2007): 47-50.
*
Carrier, Norman, and John Hobcraft.
“Demographic Estimation for Developing Societies:
A Manual of Techniques for the Detection and Reduction
of Errors in Demographic Data. London: London School of
Economics.”
Population Investigation Committee (1971).
*
Choi, Hyungwon, and Alexey I. Nesvizhskii.
“False discovery rates and related statistical concepts
in mass spectrometry-based proteomics.”
Journal of proteome research 7, no. 01 (2007): 47-50.
*
Strimmer, Korbinian.
“fdrtool: a versatile R package for estimating local
and tail area-based false discovery rates.”
Bioinformatics 24, no. 12 (2008): 1461-1462.
*
Bandelt, H-J., Päivi Lahermo, Martin Richards, and Vincent Macaulay.
“Detecting errors in mtDNA data by phylogenetic analysis.”
International journal of legal medicine 115, no. 2 (2001): 64-69.
*
Rogers, William.
“Quantile regression standard errors.”
Stata Technical Bulletin 2, no. 9 (1993).
*
Al-Marzouki, Sanaa, Stephen Evans, Tom Marshall, and Ian Roberts.
“Are these data real?
Statistical methods for the detection of data fabrication in clinical trials.”
Bmj 331, no. 7511 (2005): 267-270.
*
Glantz, STANTON A.
“Biostatistics: how to detect, correct and prevent
errors in the medical literature.”
Circulation 61, no. 1 (1980): 1-7.
*
Vail, A., and E. Gardener.
“Common statistical errors in the design and analysis
of subfertility trials.”
Human Reproduction 18, no. 5 (2003): 1000-1004.
*
Nuzzo, Regina.
“Statistical errors.”
Nature 506, no. 7487 (2014): 150-152.
*
York, Derek.
“Least squares fitting of a straight line with correlated errors.”
Earth and planetary science letters 5 (1968): 320-324.
*
Straatsma, T. P., H. J. C. Berendsen, and A. J. Stam.
“Estimation of statistical errors in molecular simulation calculations.”
Molecular Physics 57, no. 1 (1986): 89-95.
*
Todd, John A.
“Statistical false positive or true disease pathway?.”
Nature genetics 38, no. 7 (2006): 731-733.
*
Stock, James H., and Mark W. Watson.
“Heteroskedasticity‐robust standard errors
for fixed effects panel data regression.”
Econometrica 76, no. 1 (2008): 155-174
*
Brody, James P., Brian A. Williams, Barbara J. Wold, and Stephen R. Quake.
“Significance and statistical errors in the analysis of DNA microarray data.”
Proceedings of the National Academy of Sciences 99, no. 20 (2002): 12975-12978.
*
Moonesinghe, Ramal, Muin J. Khoury, and A. Cecile JW Janssens.
“Most published research findings are false—
but a little replication goes a long way.”
PLoS Med 4, no. 2 (2007): e28.
*
Van Leeuwen, Floor.
“Validation of the new Hipparcos reduction.”
Astronomy and Astrophysics 474, no. 2 (2007): 653-664.
*
Ludwig, K. R.
“Mathematical–statistical treatment of data and errors
for 230Th/U geochronology.”
Reviews in Mineralogy and Geochemistry
52, no. 1 (2003): 631-656.
*
Gay, J. D., L. D. Donaldson, and J. R. Goellner.
“False-negative results in cervical cytologic studies.”
Acta cytologica 29, no. 6 (1984): 1043-1046.
*
Obraztsov, V. F.
“Confidence limits for processes with small statistics in several subchannels
and with measurement errors.”
Nuclear Instruments and Methods in Physics Research Section A:
Accelerators, Spectrometers, Detectors and Associated Equipment
316, no. 2-3 (1992): 388-390.
*
Behm, Harriet L., and John G. Wagner.
“Errors in interpretation of data
from equilibrium dialysis protein binding experiments.”
Research communications in chemical pathology and pharmacology
26, no. 1 (1979): 145-160.
*
Pollitt, R. J., A. Green, C. J. McCabe, A. Booth, N. J. Cooper, J. V. Leonard, J.
Nicholl, P. Nicholson, J. R. Tunaley, and N. K. Virdi.
“Neonatal screening for inborn errors of metabolism:
cost, yield and outcome.”
Health technology assessment (Winchester, England) 1, no. 7 (1996): i-iv.
*
Thomas, Eric J., and Laura A. Petersen.
“Measuring errors and adverse events in health care.”
Journal of general internal medicine 18, no. 1 (2003): 61-67.
*
Armstrong, J. Scott, and Terry S. Overton.
“Estimating nonresponse bias in mail surveys.”
Journal of marketing research (1977): 396-402.
*
Hoel, David G., Elaine Ron, Randy Carter, and Kiyohiko Mabuchi.
“Influence of death certificate errors on cancer mortality trends.”
Journal of the National Cancer Institute 85, no. 13 (1993): 1063-1068.
*
Good, Phillip I., and James W. Hardin.
Common errors in statistics (and how to avoid them).
John Wiley & Sons, 2012.
*
Dovey, S. M., D. S. Meyers, R. L. Phillips, L. A. Green, G. E. Fryer,
- M. Galliher, J. Kappus, and P. Grob.
“A preliminary taxonomy of medical errors in family practice.”
Quality and safety in health care 11, no. 3 (2002): 233-238.
*
Lubin, Jay H., John D. Boice Jr, and Jonathan M. Samet.
“Errors in exposure assessment, statistical power and
the interpretation of residential radon studies.”
Radiation research 144, no. 3 (1995): 329-341.
*
Lash, Timothy L., and Aliza K. Fink.
“Semi-automated sensitivity analysis to assess systematic errors
in observational data.”
Epidemiology 14, no. 4 (2003): 451-458.
*
Templeton, Alan R.
“Statistical phylogeography:
methods of evaluating and minimizing inference errors.”
Molecular Ecology 13, no. 4 (2004): 789-809.
*
Grant, Gregory R., Junmin Liu, and Christian J. Stoeckert.
“A practical false discovery rate approach to identifying patterns
of differential expression in microarray data.”
Bioinformatics 21, no. 11 (2005): 2684-2690.
*
Gould, William.
“Quantile regression with bootstrapped standard errors.”
Stata Technical Bulletin 2, no. 9 (1993).
*
Grant, Gregory R., Junmin Liu, and Christian J. Stoeckert.
“A practical false discovery rate approach to identifying patterns
of differential expression in microarray data.”
Bioinformatics 21, no. 11 (2005): 2684-2690.
*
Gould, William.
“Quantile regression with bootstrapped standard errors.”
Stata Technical Bulletin 2, no. 9 (1993).
*
Korn, Edward L., James F. Troendle, Lisa M. McShane, and Richard Simon.
“Controlling the number of false discoveries: application to
high-dimensional genomic data.”
Journal of Statistical Planning and Inference 124, no. 2 (2004): 379-398.
*
Sonderegger-lseli, Katharina, Stefanie Burger, Jörg Muntwyler,
and Franco Salomon.
“Diagnostic errors in three medical eras: a necropsy study.”
The Lancet 355, no. 9220 (2000): 2027-2031.
*
Rosner, William.
“Errors in the Measurement of Plasma Free Testosterone 1.”
The Journal of Clinical Endocrinology and Metabolism
82, no. 6 (1997): 2014-2015.
*
Kraemer, Helena C., and Christine M. Blasey.
“Centring in regression analyses: a strategy to prevent errors
in statistical inference.”
International journal of methods in psychiatric research 13, no. 3 (2004): 141-151.
*
Sobel, Eric, Jeanette C. Papp, and Kenneth Lange.
“Detection and integration of genotyping errors in statistical genetics.”
The American Journal of Human Genetics 70, no. 2 (2002): 496-508.
*
McDonald, Clement J., Michael Weiner, and Siu L. Hui.
“Deaths due to medical errors are exaggerated
in Institute of Medicine report.”
JAMA 284, no. 1 (2000): 93-95.
*
Maes, WHd, Wouter MJ Achten, and Bart Muys.
“Use of inadequate data and methodological errors
lead to an overestimation of the water footprint of Jatropha curcas.”
Proceedings of the National Academy of Sciences
106, no. 34 (2009): E91-E91.
*
Gonzalez, Maria E., Jack L. Ogus, Gary Shapiro, and Benjamin J. Tepping.
“Standards for discussion and presentation of errors
in survey and census data.”
Journal of the American Statistical Association
70, no. 351b (1975): 5-23.
*
Wiedemayer, H., I. E. Sandalcioglu, W. Armbruster, J. Regel,
- Schaefer, and D. Stolke.
“False negative findings in intraoperative SEP monitoring:
analysis of 658 consecutive neurosurgical cases and review
of published reports.”
Journal of Neurology, Neurosurgery & Psychiatry
75, no. 2 (2004): 280-286.
*
Hubbard, Raymond, and María Jesús Bayarri.
“Confusion over measures of evidence (p’s) versus errors (α’s)
in classical statistical testing.”
The American Statistician 57, no. 3 (2003): 171-178.
*
Desmet, P. J. J.
“Effects of interpolation errors on the analysis of DEMs.”
Earth surface processes and landforms 22, no. 6 (1997): 563-580.
*
Salkever, David S.
“The use of dummy variables to compute predictions, prediction errors,
and confidence intervals.”
Journal of econometrics 4, no. 4 (1976): 393-397.
*
Goodman, Steven, and Sander Greenland.
“Why most published research findings are false: problems in the analysis.”
PLoS Med 4, no. 4 (2007): e168.
*
Brookes, S. T., E. Whitley, T. J. Peters, P. A. Mulheran, M. Egger,
and G. Davey Smith.
“Subgroup analyses in randomised controlled trials:
quantifying the risks of false-positives and false-negatives.”
Health Technology Assessment 5, no. 33 (2001): 1-56.
*
Ye, Fan, Haiyun Luo, Songwu Lu, and Lixia Zhang.
“Statistical en-route filtering of injected false data in sensor networks.”
IEEE Journal on Selected Areas in Communications
23, no. 4 (2005): 839-850.
*
Šesták, J. ”
Errors of kinetic data obtained from thermogravimetric curves
at increasing temperature.”
Talanta 13, no. 4 (1966): 567-579.
*
Šesták, J.
“Errors of kinetic data obtained from thermogravimetric curves
at increasing temperature.”
Talanta 13, no. 4 (1966): 567-579.
*
Bernadinelli, L., Cristian Pascutto, N. G. Best, and W. R. Gilks.
“Disease mapping with errors in covariates.”
Statistics in Medicine 16, no. 7 (1997): 741-752.
*
Amemiya, Yasuo.
“Instrumental variable estimator for the nonlinear
errors-in-variables model.”
Journal of Econometrics 28, no. 3 (1985): 273-289.
*
Silberstein, Adriana R., and Stuart Scott.
“Expenditure diary surveys and their associated errors.”
Measurement errors in surveys (1991): 303-326.
*
McCallum, G.J. and Coote, G.E., 1975.
“Systematic errors in transition intensities of 56Co and 66Ga.”
Nuclear Instruments and Methods, 124(1), pp.309-311.
*
Tarokh, Vahid, Ayman Naguib, Nambi Seshadri, and A. Robert Calderbank.
“Space-time codes for high data rate wireless communication: performance
criteria in the presence of channel estimation errors, mobility, and
multiple paths.”
IEEE Transactions on Communications 47, no. 2 (1999): 199-207.
*
O’Donnell, Kerry, Elizabeth Cigelnik, Nancy S. Weber, and James M. Trappe.
“Phylogenetic relationships among ascomycetous truffles and
the true and false morels inferred from 18S and
28S ribosomal DNA sequence analysis.”
Mycologia (1997): 48-65.
*
Hox, Joop J., Edith D. de Leeuw, and Ita GG Kreft.
“The effect of interviewer and respondent characteristics
on the quality of survey data: a multilevel model.”
Measurement errors in surveys (1991): 439-461.
*
Keck, Cornelia M., and Rainer H. Müller.
“Size analysis of submicron particles by laser diffractometry—
90% of the published measurements are false.”
International journal of pharmaceutics 355, no. 1 (2008): 150-163.
*
Ellestad, Myrvin H., Saul Savitz, David Bergdall, and James Teske.
“The false positive stress test: multivariate analysis
of 215 subjects with hemodynamic, angiographic and clinical data.”
The American journal of cardiology 40, no. 5 (1977): 681-685.
*
Strasak, Alexander M., Qamruz Zaman, Karl P. Pfeiffer, G. Gobel,
and Hanno Ulmer.
“Statistical errors in medical research-a review of common pitfalls.”
Swiss medical weekly 137, no. 3/4 (2007): 44.
*
Wacholder, Sholom, Stephen Chanock, Montserrat Garcia-Closas,
and Nathaniel Rothman.
“Assessing the probability that a positive report is false:
an approach for molecular epidemiology studies.”
Journal of the National Cancer Institute 96, no. 6 (2004): 434-442.
*
Li, Jun, Daniela M. Witten, Iain M. Johnstone, and Robert Tibshirani.
“Normalization, testing, and false discovery rate estimation
for RNA-sequencing data.”
Biostatistics (2011): kxr031.
*
Thompson, B., 1998.
“Five Methodology Errors in Educational Research:
The Pantheon of Statistical Significance and Other Faux Pas.”
*
Common data analysis errors in batch adsorption studies
El-Khaiary, Mohammad I.
Hydrometallurgy
0304-386X
01/2011 Volume: 105 Issue: 3-4 Page: 314-320
10.1016/j.hydromet.2010.11.005
*
Buscemi, Nina, Lisa Hartling, Ben Vandermeer, Lisa Tjosvold,
and Terry P. Klassen.
“Single data extraction generated more errors than
double data extraction in systematic reviews.”
Journal of clinical epidemiology 59, no. 7 (2006): 697-703.
*
Chib, Siddhartha, and Edward Greenberg.
“Hierarchical analysis of SUR models with extensions
to correlated serial errors and time-varying parameter models.”
Journal of Econometrics 68, no. 2 (1995): 339-360.
*
Zech, Gunter.
“Upper limits in experiments with background or measurement errors.”
Nuclear Instruments and Methods in Physics Research Section A:
Accelerators, Spectrometers, Detectors and Associated Equipment
277, no. 2-3 (1989): 608-610.
*
Jass, J. R., K. A. Do, L. A. Simms, H. Iino, C. Wynter, S. P. Pillay, J. Searle,
- Radford-Smith, J. Young, and B. Leggett. “
Morphology of sporadic colorectal cancer with DNA replication errors.”
Gut 42, no. 5 (1998): 673-679.
*
Kessel, Julie B., and Mark Zimmerman.
“Reporting errors in studies of the diagnostic performance
of self-administered questionnaires: extent of the problem,
recommendations for standardized presentation of results,
and implications for the peer review process.”
Psychological Assessment 5, no. 4 (1993): 395.
*
Ficetola, Gentile F., Johan Pansu, Aurélie Bonin, Eric Coissac, Charline Giguet‐Covex, Marta De Barba, Ludovic Gielly et al.
“Replication levels, false presences and the estimation
of the presence/absence from eDNA metabarcoding data.”
Molecular Ecology Resources 15, no. 3 (2015): 543-556.
*
Paturel, J. E., E. Servat, and A. Vassiliadis.
“Sensitivity of conceptual rainfall-runoff algorithms to errors in input data—
case of the GR2M model.”
Journal of hydrology 168, no. 1 (1995): 111-125.
*
Sörbom, Dag.
“Detection of correlated errors in longitudinal data.”
British Journal of Mathematical and Statistical Psychology
28, no. 2 (1975): 138-151.
*
Leunens, G., Johan Verstraete, Walter Van den Bogaert, Jan Van Dam,
- Dutreix, and E. Van der Schueren.
“Human errors in data transfer during the preparation and delivery
of radiation treatment affecting the final result:“garbage in, garbage out”.”
Radiotherapy and Oncology 23, no. 4 (1992): 217-222.
*
Alper, Joseph S., and Robert I. Gelb.
“Standard errors and confidence intervals in nonlinear regression:
comparison of Monte Carlo and parametric statistics.”
Journal of Physical Chemistry 94, no. 11 (1990): 4747-4751.
*
Torrance‐Rynard, Vicki L., and Stephen D. Walter.
“Effects of dependent errors in the assessment
of diagnostic test performance.”
Statistics in medicine 16, no. 19 (1997): 2157-2175.
*
Raykov, Tenko.
“A method for obtaining standard errors and confidence intervals
of composite reliability for congeneric items.”
Applied Psychological Measurement 22, no. 4 (1998): 369-374.
*
Anderson, B. D. O., and M. Deistler.
“Identifiability in Dynamic Errors‐in‐Variables Models.”
Journal of Time Series Analysis 5, no. 1 (1984): 1-13.
*
Liu, Yao, Peng Ning, and Michael K. Reiter.
“False data injection attacks against state estimation
in electric power grids.”
ACM Transactions on Information and System Security
(TISSEC) 14, no. 1 (2011): 13.
*
Biemer, Paul, and S. Lynne Stokes.
“Approaches to the modeling of measurement errors.”
Measurement errors in surveys (1991): 485-516.
*
Quarry, [ 9] MA, R. L. Grob, and L. R. Snyder.
“Prediction of precise isocratic retention data from two or more gradient
elution runs. Analysis of some associated errors.”
Analytical Chemistry 58, no. 4 (1986): 907-917.
*
Graham, Catherine H., Jane Elith, Robert J. Hijmans, Antoine Guisan,
- Townsend Peterson, and Bette A. Loiselle.
“The influence of spatial errors in species occurrence data used in distribution models.”
Journal of Applied Ecology 45, no. 1 (2008): 239-247.
*
King, Gary.
“How not to lie with statistics:
Avoiding common mistakes in quantitative political science.”
American Journal of Political Science (1986): 666-687.
*
Karp, Natasha A., Paul S. McCormick, Matthew R. Russell, and Kathryn S. Lilley.
“Experimental and statistical considerations to avoid false conclusions
in proteomics studies using differential in-gel electrophoresis.”
Molecular and Cellular Proteomics 6, no. 8 (2007): 1354-1364.
*
Yu, J.X., Chong, Z., Lu, H. and Zhou, A.,
2004, August.
“False positive or false negative: mining frequent itemsets from high speed
transactional data streams.”
In Proceedings of the Thirtieth international conference on
Very large data bases-
Volume 30 (pp. 204-215). VLDB Endowment.
*
Bartel, Paul, CHENG-TING Chien, R. Sternglanz, and Stanley Fields.
“Elimination of false positives that arise in using the two-hybrid system.”
Biotechniques 14, no. 6 (1993): 920-924.
*
DeWoody, Jennifer, John D. Nason, and Valerie D. Hipkins.
“Mitigating scoring errors in microsatellite data from wild populations.”
Molecular Ecology Notes 6, no. 4 (2006): 951-957.
*
Khoussainova, Nodira, Magdalena Balazinska, and Dan Suciu.
“Towards correcting input data errors probabilistically
using integrity constraints.”
In Proceedings of the 5th ACM international workshop on
Data engineering for wireless and mobile access,
- 43-50. ACM, 2006.
*
Hackett, C. A., and L. B. Broadfoot.
“Effects of genotyping errors, missing values and segregation
distortion in molecular marker data on the construction
of linkage maps.”
Heredity 90, no. 1 (2003): 33-38.
*
Borgia, G. C., R. J. S. Brown, and P. Fantazzini.
“Uniform-penalty inversion of multiexponential decay data: II.
Data spacing, T2 data, systematic data errors, and diagnostics.”
Journal of Magnetic Resonance 147, no. 2 (2000): 273-285.
*
Batanero, Carmen, Juan D. Godino, A. Vallecillos, D. R. Green,
and P. Holmes.
“Errors and difficulties in understanding elementary statistical concepts.”
International Journal of Mathematical Education in Science and Technology
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