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Showing 1 to 12 of 14 entries
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Understanding and estimating the power to detect cross-level interaction effects in multilevel modeling.

The Journal of applied psychology

Mathieu JE, Aguinis H, Culpepper SA, Chen G.
PMID: 22582726
J Appl Psychol. 2012 Sep;97(5):951-66. doi: 10.1037/a0028380. Epub 2012 May 14.

Cross-level interaction effects lie at the heart of multilevel contingency and interactionism theories. Researchers have often lamented the difficulty of finding hypothesized cross-level interactions, and to date there has been no means by which the statistical power of such...

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Mathieu JE, Aguinis H, Culpepper SA, et al. Understanding and estimating the power to detect cross-level interaction effects in multilevel modeling. J Appl Psychol. 2012;97(5):951-66doi: 10.1037/a0028380.
Mathieu, J. E., Aguinis, H., Culpepper, S. A., & Chen, G. (2012). Understanding and estimating the power to detect cross-level interaction effects in multilevel modeling. The Journal of applied psychology, 97(5), 951-66. https://doi.org/10.1037/a0028380
Mathieu, John E, et al. "Understanding and estimating the power to detect cross-level interaction effects in multilevel modeling." The Journal of applied psychology vol. 97,5 (2012): 951-66. doi: https://doi.org/10.1037/a0028380
Mathieu JE, Aguinis H, Culpepper SA, Chen G. Understanding and estimating the power to detect cross-level interaction effects in multilevel modeling. J Appl Psychol. 2012 Sep;97(5):951-66. doi: 10.1037/a0028380. Epub 2012 May 14. PMID: 22582726.
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Local isotropic diffusion approximation for coupled internal and overall molecular motions in NMR spin relaxation.

The journal of physical chemistry. B

Gill ML, Palmer AG.
PMID: 25167331
J Phys Chem B. 2014 Sep 25;118(38):11120-8. doi: 10.1021/jp506580c. Epub 2014 Sep 11.

The present work demonstrates that NMR spin relaxation rate constants for molecules interconverting between states with different diffusion tensors can be modeled theoretically by combining orientational correlation functions for exchanging spherical molecules with locally isotropic approximations for the diffusion...

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Gill ML, Palmer AG. Local isotropic diffusion approximation for coupled internal and overall molecular motions in NMR spin relaxation. J Phys Chem B. 2014;118(38):11120-8doi: 10.1021/jp506580c.
Gill, M. L., & Palmer, A. G. (2014). Local isotropic diffusion approximation for coupled internal and overall molecular motions in NMR spin relaxation. The journal of physical chemistry. B, 118(38), 11120-8. https://doi.org/10.1021/jp506580c
Gill, Michelle L, and Palmer, Arthur G. "Local isotropic diffusion approximation for coupled internal and overall molecular motions in NMR spin relaxation." The journal of physical chemistry. B vol. 118,38 (2014): 11120-8. doi: https://doi.org/10.1021/jp506580c
Gill ML, Palmer AG. Local isotropic diffusion approximation for coupled internal and overall molecular motions in NMR spin relaxation. J Phys Chem B. 2014 Sep 25;118(38):11120-8. doi: 10.1021/jp506580c. Epub 2014 Sep 11. PMID: 25167331; PMCID: PMC4174990.
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Simplified molecular input line entry system-based optimal descriptors: QSAR modelling for voltage-gated potassium channel subunit Kv7.2.

SAR and QSAR in environmental research

Achary PG.
PMID: 24580100
SAR QSAR Environ Res. 2014;25(1):73-90. doi: 10.1080/1062936X.2013.842930. Epub 2014 Mar 03.

CORAL software has been used to build quantitative structure-activity relationships (QSARs) for the prediction of binding affinities (pEC50, i.e., minus decimal logarithm of the 50% effective concentration) of 35 potent inhibitors towards the voltage-gated potassium channel subunit Kv7.2. The...

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Achary PG. Simplified molecular input line entry system-based optimal descriptors: QSAR modelling for voltage-gated potassium channel subunit Kv7.2. SAR QSAR Environ Res. 2014;25(1):73-90doi: 10.1080/1062936X.2013.842930.
Achary, P. G. (2014). Simplified molecular input line entry system-based optimal descriptors: QSAR modelling for voltage-gated potassium channel subunit Kv7.2. SAR and QSAR in environmental research, 25(1), 73-90. https://doi.org/10.1080/1062936X.2013.842930
Achary, P Ganga Raju. "Simplified molecular input line entry system-based optimal descriptors: QSAR modelling for voltage-gated potassium channel subunit Kv7.2." SAR and QSAR in environmental research vol. 25,1 (2014): 73-90. doi: https://doi.org/10.1080/1062936X.2013.842930
Achary PG. Simplified molecular input line entry system-based optimal descriptors: QSAR modelling for voltage-gated potassium channel subunit Kv7.2. SAR QSAR Environ Res. 2014;25(1):73-90. doi: 10.1080/1062936X.2013.842930. Epub 2014 Mar 03. PMID: 24580100.
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New theory for distribution of minimum resolution in multi-component separations with noise/detection limits.

Journal of chromatography. A

Davis JM.
PMID: 22771062
J Chromatogr A. 2012 Aug 17;1251:1-9. doi: 10.1016/j.chroma.2012.06.034. Epub 2012 Jun 19.

Equations were proposed recently for computing the distribution of minimum resolution (resolution distribution) of two Gaussian peaks with equal standard deviations, when peak heights in a multi-component separation follow a statistical distribution. The computation depended on the survival function...

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Davis JM. New theory for distribution of minimum resolution in multi-component separations with noise/detection limits. J Chromatogr A. 2012;1251:1-9doi: 10.1016/j.chroma.2012.06.034.
Davis, J. M. (2012). New theory for distribution of minimum resolution in multi-component separations with noise/detection limits. Journal of chromatography. A, 12511-9. https://doi.org/10.1016/j.chroma.2012.06.034
Davis, Joe M. "New theory for distribution of minimum resolution in multi-component separations with noise/detection limits." Journal of chromatography. A vol. 1251 (2012): 1-9. doi: https://doi.org/10.1016/j.chroma.2012.06.034
Davis JM. New theory for distribution of minimum resolution in multi-component separations with noise/detection limits. J Chromatogr A. 2012 Aug 17;1251:1-9. doi: 10.1016/j.chroma.2012.06.034. Epub 2012 Jun 19. PMID: 22771062.
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A Monte Carlo simulation based two-stage adaptive resonance theory mapping approach for offshore oil spill vulnerability index classification.

Marine pollution bulletin

Li P, Chen B, Li Z, Zheng X, Wu H, Jing L, Lee K.
PMID: 25044043
Mar Pollut Bull. 2014 Sep 15;86(1):434-442. doi: 10.1016/j.marpolbul.2014.06.036. Epub 2014 Jul 17.

In this paper, a Monte Carlo simulation based two-stage adaptive resonance theory mapping (MC-TSAM) model was developed to classify a given site into distinguished zones representing different levels of offshore Oil Spill Vulnerability Index (OSVI). It consisted of an...

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Li P, Chen B, Li Z, et al. A Monte Carlo simulation based two-stage adaptive resonance theory mapping approach for offshore oil spill vulnerability index classification. Mar Pollut Bull. 2014;86(1):434-442doi: 10.1016/j.marpolbul.2014.06.036.
Li, P., Chen, B., Li, Z., Zheng, X., Wu, H., Jing, L., & Lee, K. (2014). A Monte Carlo simulation based two-stage adaptive resonance theory mapping approach for offshore oil spill vulnerability index classification. Marine pollution bulletin, 86(1), 434-442. https://doi.org/10.1016/j.marpolbul.2014.06.036
Li, Pu, et al. "A Monte Carlo simulation based two-stage adaptive resonance theory mapping approach for offshore oil spill vulnerability index classification." Marine pollution bulletin vol. 86,1 (2014): 434-442. doi: https://doi.org/10.1016/j.marpolbul.2014.06.036
Li P, Chen B, Li Z, Zheng X, Wu H, Jing L, Lee K. A Monte Carlo simulation based two-stage adaptive resonance theory mapping approach for offshore oil spill vulnerability index classification. Mar Pollut Bull. 2014 Sep 15;86(1):434-442. doi: 10.1016/j.marpolbul.2014.06.036. Epub 2014 Jul 17. PMID: 25044043.
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[Influence of group sample size on statistical power of tests for quantitative data with an imbalanced design].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University

Liang Q, Yu X, An S.
PMID: 32897205
Nan Fang Yi Ke Da Xue Xue Bao. 2020 May 30;40(5):713-717. doi: 10.12122/j.issn.1673-4254.2020.05.16.

OBJECTIVE: To explore the relationship between sample size in the groups and statistical power of ANOVA and Kruskal-Wallis METHODS: The sample sizes of the two tests were estimated by SAS program with given parameter settings, and Monte Carlo simulation...

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Liang Q, Yu X, An S. [Influence of group sample size on statistical power of tests for quantitative data with an imbalanced design]. Nan Fang Yi Ke Da Xue Xue Bao. 2020;40(5):713-717doi: 10.12122/j.issn.1673-4254.2020.05.16.
Liang, Q., Yu, X., & An, S. (2020). [Influence of group sample size on statistical power of tests for quantitative data with an imbalanced design]. Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 40(5), 713-717. https://doi.org/10.12122/j.issn.1673-4254.2020.05.16
Liang, Qihong, et al. "[Influence of group sample size on statistical power of tests for quantitative data with an imbalanced design]." Nan fang yi ke da xue xue bao = Journal of Southern Medical University vol. 40,5 (2020): 713-717. doi: https://doi.org/10.12122/j.issn.1673-4254.2020.05.16
Liang Q, Yu X, An S. [Influence of group sample size on statistical power of tests for quantitative data with an imbalanced design]. Nan Fang Yi Ke Da Xue Xue Bao. 2020 May 30;40(5):713-717. doi: 10.12122/j.issn.1673-4254.2020.05.16. Chinese. PMID: 32897205; PMCID: PMC7277317.
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Incorporating partial adherence into the principal stratification analysis framework.

Statistics in medicine

Sanders E, Gustafson P, Karim ME.
PMID: 33880769
Stat Med. 2021 Jul 10;40(15):3625-3644. doi: 10.1002/sim.8986. Epub 2021 Apr 20.

Participants in pragmatic clinical trials often partially adhere to treatment. However, to simplify the analysis, most studies dichotomize adherence (supposing that subjects received either full or no treatment), which can introduce biases in the results. For example, the popular...

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Sanders E, Gustafson P, Karim ME. Incorporating partial adherence into the principal stratification analysis framework. Stat Med. 2021;40(15):3625-3644doi: 10.1002/sim.8986.
Sanders, E., Gustafson, P., & Karim, M. E. (2021). Incorporating partial adherence into the principal stratification analysis framework. Statistics in medicine, 40(15), 3625-3644. https://doi.org/10.1002/sim.8986
Sanders, Eric, et al. "Incorporating partial adherence into the principal stratification analysis framework." Statistics in medicine vol. 40,15 (2021): 3625-3644. doi: https://doi.org/10.1002/sim.8986
Sanders E, Gustafson P, Karim ME. Incorporating partial adherence into the principal stratification analysis framework. Stat Med. 2021 Jul 10;40(15):3625-3644. doi: 10.1002/sim.8986. Epub 2021 Apr 20. PMID: 33880769.
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Sequential change point detection for high-dimensional data using nonconvex penalized quantile regression.

Biometrical journal. Biometrische Zeitschrift

Ratnasingam S, Ning W.
PMID: 33191556
Biom J. 2021 Mar;63(3):575-598. doi: 10.1002/bimj.202000078. Epub 2020 Nov 16.

In this paper, a sequential change point detection method is developed to monitor structural change in smoothly clipped absolute deviation (SCAD) penalized quantile regression (SPQR) models. The asymptotic properties of the test statistic are derived from the null and...

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Ratnasingam S, Ning W. Sequential change point detection for high-dimensional data using nonconvex penalized quantile regression. Biom J. 2020;63(3):575-598doi: 10.1002/bimj.202000078.
Ratnasingam, S., & Ning, W. (2021). Sequential change point detection for high-dimensional data using nonconvex penalized quantile regression. Biometrical journal. Biometrische Zeitschrift, 63(3), 575-598. https://doi.org/10.1002/bimj.202000078
Ratnasingam, Suthakaran, and Ning, Wei. "Sequential change point detection for high-dimensional data using nonconvex penalized quantile regression." Biometrical journal. Biometrische Zeitschrift vol. 63,3 (2021): 575-598. doi: https://doi.org/10.1002/bimj.202000078
Ratnasingam S, Ning W. Sequential change point detection for high-dimensional data using nonconvex penalized quantile regression. Biom J. 2021 Mar;63(3):575-598. doi: 10.1002/bimj.202000078. Epub 2020 Nov 16. PMID: 33191556.
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Space-time shape uncertainties in the forward and inverse problem of electrocardiography.

International journal for numerical methods in biomedical engineering

Gander L, Krause R, Multerer M, Pezzuto S.
PMID: 34410040
Int J Numer Method Biomed Eng. 2021 Oct;37(10):e3522. doi: 10.1002/cnm.3522. Epub 2021 Sep 08.

In electrocardiography, the "classic" inverse problem is the reconstruction of electric potentials at a surface enclosing the heart from remote recordings at the body surface and an accurate description of the anatomy. The latter being affected by noise and...

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Gander L, Krause R, Multerer M, et al. Space-time shape uncertainties in the forward and inverse problem of electrocardiography. Int J Numer Method Biomed Eng. 2021;37(10):e3522doi: 10.1002/cnm.3522.
Gander, L., Krause, R., Multerer, M., & Pezzuto, S. (2021). Space-time shape uncertainties in the forward and inverse problem of electrocardiography. International journal for numerical methods in biomedical engineering, 37(10), e3522. https://doi.org/10.1002/cnm.3522
Gander, Lia, et al. "Space-time shape uncertainties in the forward and inverse problem of electrocardiography." International journal for numerical methods in biomedical engineering vol. 37,10 (2021): e3522. doi: https://doi.org/10.1002/cnm.3522
Gander L, Krause R, Multerer M, Pezzuto S. Space-time shape uncertainties in the forward and inverse problem of electrocardiography. Int J Numer Method Biomed Eng. 2021 Oct;37(10):e3522. doi: 10.1002/cnm.3522. Epub 2021 Sep 08. PMID: 34410040.
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Exact change point detection with improved power in small-sample binomial sequences.

Biometrical journal. Biometrische Zeitschrift

Ellenberger D, Lausen B, Friede T.
PMID: 33151005
Biom J. 2021 Mar;63(3):558-574. doi: 10.1002/bimj.201900273. Epub 2020 Nov 05.

To detect a change in the probability of a sequence of independent binomial random variables, a variety of asymptotic and exact testing procedures have been proposed. Whenever the sample size or the event rate is small, asymptotic approximations of...

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Ellenberger D, Lausen B, Friede T. Exact change point detection with improved power in small-sample binomial sequences. Biom J. 2020;63(3):558-574doi: 10.1002/bimj.201900273.
Ellenberger, D., Lausen, B., & Friede, T. (2021). Exact change point detection with improved power in small-sample binomial sequences. Biometrical journal. Biometrische Zeitschrift, 63(3), 558-574. https://doi.org/10.1002/bimj.201900273
Ellenberger, David, et al. "Exact change point detection with improved power in small-sample binomial sequences." Biometrical journal. Biometrische Zeitschrift vol. 63,3 (2021): 558-574. doi: https://doi.org/10.1002/bimj.201900273
Ellenberger D, Lausen B, Friede T. Exact change point detection with improved power in small-sample binomial sequences. Biom J. 2021 Mar;63(3):558-574. doi: 10.1002/bimj.201900273. Epub 2020 Nov 05. PMID: 33151005.
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BOLD sensitivity and vessel size specificity along CPMG and GRASE echo trains.

Magnetic resonance in medicine

Scheffler K, Engelmann J, Heule R.
PMID: 34056746
Magn Reson Med. 2021 Oct;86(4):2076-2083. doi: 10.1002/mrm.28871. Epub 2021 May 31.

PURPOSE: To assess the vessel size specificity and sensitivity of rapid CPMG and GRASE for functional BOLD imaging for different echo train lengths, echo spacings, field strength, and refocusing flip angle schemes. In addition, the behavior of signals acquired...

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Scheffler K, Engelmann J, Heule R. BOLD sensitivity and vessel size specificity along CPMG and GRASE echo trains. Magn Reson Med. 2021;86(4):2076-2083doi: 10.1002/mrm.28871.
Scheffler, K., Engelmann, J., & Heule, R. (2021). BOLD sensitivity and vessel size specificity along CPMG and GRASE echo trains. Magnetic resonance in medicine, 86(4), 2076-2083. https://doi.org/10.1002/mrm.28871
Scheffler, Klaus, et al. "BOLD sensitivity and vessel size specificity along CPMG and GRASE echo trains." Magnetic resonance in medicine vol. 86,4 (2021): 2076-2083. doi: https://doi.org/10.1002/mrm.28871
Scheffler K, Engelmann J, Heule R. BOLD sensitivity and vessel size specificity along CPMG and GRASE echo trains. Magn Reson Med. 2021 Oct;86(4):2076-2083. doi: 10.1002/mrm.28871. Epub 2021 May 31. PMID: 34056746.
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Deterministic sensitivity analysis for first-order Monte Carlo simulations: a technical note.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research

Geisler BP, Siebert U, Gazelle GS, Cohen DJ, Göhler A.
PMID: 18647259
Value Health. 2009 Jan-Feb;12(1):96-7. doi: 10.1111/j.1524-4733.2008.00411.x. Epub 2008 Jul 18.

OBJECTIVES: Monte Carlo microsimulations have gained increasing popularity in decision-analytic modeling because they can incorporate discrete events. Although deterministic sensitivity analyses are essential for interpretation of results, it remains difficult to combine these alongside Monte Carlo simulations in standard...

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Geisler BP, Siebert U, Gazelle GS, et al. Deterministic sensitivity analysis for first-order Monte Carlo simulations: a technical note. Value Health. 2008;12(1):96-7doi: 10.1111/j.1524-4733.2008.00411.x.
Geisler, B. P., Siebert, U., Gazelle, G. S., Cohen, D. J., & Göhler, A. (2009). Deterministic sensitivity analysis for first-order Monte Carlo simulations: a technical note. Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research, 12(1), 96-7. https://doi.org/10.1111/j.1524-4733.2008.00411.x
Geisler, Benjamin P, et al. "Deterministic sensitivity analysis for first-order Monte Carlo simulations: a technical note." Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research vol. 12,1 (2009): 96-7. doi: https://doi.org/10.1111/j.1524-4733.2008.00411.x
Geisler BP, Siebert U, Gazelle GS, Cohen DJ, Göhler A. Deterministic sensitivity analysis for first-order Monte Carlo simulations: a technical note. Value Health. 2009 Jan-Feb;12(1):96-7. doi: 10.1111/j.1524-4733.2008.00411.x. Epub 2008 Jul 18. PMID: 18647259.
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Showing 1 to 12 of 14 entries