Associate Professor Samuel Mueller

F07 - Carslaw Building
The University of Sydney

Telephone 9036 7878
Fax 9351 4534

Website Google Scholar
Curriculum vitae Curriculum vitae

Biographical details

Selected Professional Service

  • Associate Dean Research Education, since 2017: for 900+ students and their supervisors
  • Associate Dean Postgraduate Research, 2016: for 600+ students and their supervisors
  • President, Australasian Region of the International Biometric Society, 2017-18
  • President-elect, Australasian Region of the International Biometric Society, 2016
  • Postgraduate Director, School of Mathematics and Statistics, USyd, 2012-15

Editorial Appointments

  • Theory and Methods Editor, Australian and New Zealand Journal of Statistics, since 2017
  • Guest Editor, Computational Statistics and Data Analysis (CSDA), 2015-16
  • Associate Editor, Computational Statistics and Data Analysis, since 2016
  • Associate Editor, Econometrics and Statistics, since 2016
  • Associate Editor, Australian and New Zealand Journal of Statistics, 2013-17

Bio Sketch

Samuel Müller is a statistician with expertise in variable selection and inference for statistically challenging data. He is an Associate Professor in the School of Mathematics and Statistics at the University of Sydney, the Associate Dean Research Education in the Faculty of Science, President of the Australasian Region of the International Biometric Society and a Theory and Methods Editor of the Australian and New Zealand Journal of Statistics. He joined the University of Sydney in 2008 after previous appointments that included a postdoc at the ANU (2003-2004) as well as academic positions at the University of Bern (2004-06) and the University of Western Australia (2006-2008).

Research interests

Samuel Müller is a member of the Statistics Research Group. His research is motivated by complex data, including for longitudinal, clustered and correlated univariate and multivariate responses; classification and improved prediction methods for multiplatform data in but not limited to omics data. He investigates theoretical properties of regularization methods in various asymptotic scenarios and improves these methods by learning from resampling-based stability information. He develops advanced model visualisation methods to enable interactive and dynamic model building, investigates robust selection and estimation methods in regression type models, and devises statistical methods for the analysis of multi-layered and structured data in bioinformatics, microbiome and neuroscience applications.

Teaching and supervision

Postdocs and Students

Recent short courses

Model Selection in R (10-11 April 2017 at the ANU)

This course, jointly taught with Garth Tarr, focuses on model selection techniques for linear and generalised linear regression in two scenarios: when an extensive search of the model space is possible as well as when the dimension is large and either stepwise algorithms or regularization techniques have to be employed to identify good models.

Timetable

S_Mueller

Current research students

Project title Research student
Higher Order Analysis of Mixture Model Order Selection Haruki OSAKA

Selected software and R packages

  • smoothtail (Smooth tail index estimation; JSCS 79:1155-67, 2009)
  • MonoPoly (Revisiting fitting monotone polynomials to data; Computational Statistics DOI: 10.1007/s00180-012-0390-5, 2013)
  • mplot (Graphical model stability and variable selection procedures, paper in preparation, 2015)
  • code not on CRAN

International links

United States

(Penn State University, USA) Research collaboration with Prof Yanyuan Ma

United States

(Texas A&M, USA) Research collaborations with Profs Ray Carroll, Tanya Garcia and Suojin Wang

Selected grants

2017

  • Prognosis based network-type feature extraction for complex biological data; Yang J, Mueller S, Ormerod J, Yang P, Mann G; Australian Research Council (ARC)/Discovery Projects (DP).

2014

  • Prediction, inference and their application to modelling correlated data; Welsh A, Mueller S; Australian Research Council (ARC)/Discovery Projects (DP).

2013

  • Vertically integrated statistical modelling in multi-layered omics studies; Yang J, Mueller S, Mann G; Australian Research Council (ARC)/Discovery Projects (DP).

2011

  • Building models for complex data; Welsh A, Mueller S; Australian Research Council (ARC)/Discovery Projects (DP).

Selected publications

Download citations: PDF RTF Endnote

Journals

  • Mueller, S., Boente, G., Croux, C., Romo, J., Van Elst, S. (2017). 2nd special issue on robust analysis of complex data. Computational Statistics and Data Analysis, 113, 395-397. [More Information]
  • Patrick, E., Schramm, S., Ormerod, J., Scolyer, R., Mann, G., Mueller, S., Yang, J. (2017). A multi-step classifier addressing cohort heterogeneity improves performance of prognostic biomarkers in three cancer types. Oncotarget, 8(2), 2807-2815. [More Information]
  • Hui, F., Mueller, S., Welsh, A. (2017). Hierarchical selection of fixed and random effects in generalized linear mixed models. Statistica Sinica, 27(2), 501-518. [More Information]
  • Garcia, T., Mueller, S. (2016). Cox regression with exclusion frequency-based weights to identify neuroimaging markers relevant to Huntington's disease onset. Annals of Applied Statistics, 10(4), 2130-2156. [More Information]
  • Murray, K., Mueller, S., Turlach, B. (2016). Fast and flexible methods for monotone polynomial fitting. Journal of Statistical Computation and Simulation, 86(15), 2946-2966. [More Information]
  • Jayawardana, K., Schramm, S., Tembe, V., Mueller, S., Thompson, J., Scolyer, R., Mann, G., Yang, J. (2016). Identification, Review, and Systematic Cross-Validation of microRNA Prognostic Signatures in Metastatic Melanoma. Journal of Investigative Dermatology, 136(1), 245-254. [More Information]
  • You, C., Mueller, S., Ormerod, J. (2016). On generalized degrees of freedom with application in linear mixed models selection. Statistics and Computing, 26(1), 199-210. [More Information]
  • Tarr, G., Mueller, S., Weber, N. (2016). Robust estimation of precision matrices under cellwise contamination. Computational Statistics and Data Analysis, 93, 404-420. [More Information]
  • Kaser, S., Froelicher, J., Li, Q., Muller, S., Metzger, U., Castiglione-Gertsch, M., Laffer, U., Maurer, C. (2015). Adenocarcinomas of the upper third of the rectum and the rectosigmoid junction seem to have similar prognosis as colon cancers even without radiotherapy, SAKK 40/87. Langenbecks Archives of Surgery, 400, 675-682. [More Information]
  • Jayawardana, K., Schramm, S., Haydu, L., Thompson, J., Scolyer, R., Mann, G., Mueller, S., Yang, J. (2015). Determination of prognosis in metastatic melanoma through integration of clinico-pathologic, mutation, mRNA, microRNA, and protein information. International Journal of Cancer, 136(4), 863-874. [More Information]
  • Patrick, E., Buckley, M., Mueller, S., Lin, D., Yang, J. (2015). Inferring data-specific micro-RNA function through the joint ranking of micro-RNA and pathways from matched micro-RNA and gene expression data. Bioinformatics, 31(17), 2822-2828. [More Information]
  • Mueller, S., Tarr, G. (2015). Much more than U-statistics: A symposium to celebrate Neville C. Weber. Statistical Society of Australia. Newsletter, 151, 10-12.
  • Tarr, G., Weber, N., Mueller, S. (2015). The difference of symmetric quantiles under long range dependence. Statistics and Probability Letters, 98, 144-150. [More Information]
  • Garcia, T., Mueller, S., Carroll, R., Walzem, R. (2014). Identification of important regressor groups, subgroups and individuals via regularization methods: application to gut microbiome data. Bioinformatics, 30(6), 831-837. [More Information]
  • Garcia, T., Mueller, S. (2014). Influence of Measures of Significance based Weights in the Weighted Lasso. Journal of the Indian Society of Agricultural Statistics, 68(2), 131-144.
  • You, C., Ormerod, J., Mueller, S. (2014). On Variational Bayes Estimation and Variational Bayes Information Criteria for Linear Regression Models. Australian and New Zealand Journal of Statistics, 56(1), 73-87. [More Information]
  • Oates, J., Casikar, I., Campain, A., Mueller, S., Yang, J., Reid, S., Condous, G. (2013). A prediction model for viability at the end of the first trimester after a single early pregnancy evaluation. Australian and New Zealand Journal of Obstetrics and Gynaecology, 53(1), 51-57. [More Information]
  • Sampson, J., Chatterjee, N., Carroll, R., Mueller, S. (2013). Controlling the local false discovery rate in the adaptive Lasso. Biostatistics, 14(4), 653-666. [More Information]
  • Murray, K., Heritier, S., Mueller, S. (2013). Graphical tools for model selection in generalized linear models. Statistics in Medicine, 32, 4438-4451. [More Information]
  • Mueller, S., Scealy, J., Welsh, A. (2013). Model selection in linear mixed models. Statistical Science, 28(2), 135-167. [More Information]
  • Murray, K., Mueller, S., Turlach, B. (2013). Revisiting fitting monotone polynomials to data. Computational Statistics, 28(5), 1989-2005. [More Information]
  • Garcia, T., Mueller, S., Carroll, R., Dunn, T., Thomas, A., Adams, S., Pillai, S., Walzem, R. (2013). Structured variable selection with q-values. Biostatistics, 14(4), 695-707. [More Information]
  • Tarr, G., Mueller, S., Weber, N. (2012). A robust scale estimator based on pairwise means. Journal of Nonparametric Statistics, 24(1), 187-199. [More Information]
  • Feher, K., Whelan, J., Mueller, S. (2012). Exploring Multicollinearity Using a Random Matrix Theory Approach. Statistical Applications in Genetics and Molecular Biology, 11(3), A15-1-A15-33. [More Information]
  • Firmin, L., Mueller, S., Rosler, K. (2012). The latency distribution of motor evoked potentials in patients with multiple sclerosis. Clinical Neurophysiology, 123(12), 2414-2421. [More Information]
  • Firmin, L., Mueller, S., Rosler, K. (2011). A method to measure the distribution of latencies of motor evoked potentials in man. Clinical Neurophysiology, 122, 176-182. [More Information]
  • Feher, K., Whelan, J., Mueller, S. (2011). Assessing modularity using a random matrix theory approach. Statistical Applications in Genetics and Molecular Biology, 10(1), 1-34. [More Information]
  • Martinez, J., Carroll, R., Mueller, S., Sampson, J., Chatterjee, N. (2011). Empirical Performance of Cross-Validation With Oracle Methods in a Genomics Context. The American Statistician, 65(4), 223-228. [More Information]
  • Mueller, S., Chhay, H. (2011). Partially smooth tail-index estimation for small samples. Computational Statistics, 26(3), 491-505. [More Information]
  • Tuft, K., Crowther, M., Connell, K., Mueller, S., McArthur, C. (2011). Predation risk and competitive interactions affect foraging of an endangered refuge-dependent herbivore. Animal Conservation: the rapid publication journal for quantitative studies in conservation, 14(4), 447-457. [More Information]
  • Martinez, J., Carroll, R., Mueller, S., Sampson, J., Chatterjee, N. (2010). A note on the effect on power of score tests via dimension reduction by penalized regression under the null. The International Journal of Biostatistics, 6(1), A12-1-A12-12. [More Information]
  • Mueller, S., Welsh, A. (2010). On model selection curves. International Statistical Review, 78(2), 240-256. [More Information]
  • Mueller, S., Vial, C. (2009). Partially linear model selection by the Bootstrap. Australian and New Zealand Journal of Statistics, 51(2), 183-200. [More Information]
  • Mueller, S., Welsh, A. (2009). Robust model selection in generalized linear models. Statistica Sinica, 19(3), 1155-1170. [More Information]
  • Mueller, S., Welsh, A. (2009). Robust model selection in generalized linear models (supplementary material). Statistica Sinica, 19(3), 1-5.
  • Mueller, S., Rufibach, K. (2009). Smooth tail-index estimation. Journal of Statistical Computation and Simulation, 79(9), 1155-1167. [More Information]
  • Mueller, S., Rufibach, K. (2008). On the max-domain of attraction of distributions with log-concave densities. Statistics and Probability Letters, 78, 1440-1444. [More Information]
  • Mueller, S., Conforto, A., Z’Graggen, W., Kaelin-Lang, A. (2006). Estimating the Number of Motor Units Using Random Sums with Independently Thinned Terms. Mathematical Biosciences, 202(1), 29-41. [More Information]
  • Husler, J., Li, D., Mueller, S. (2006). Weighted Least Squares Estimation of the Extreme Value Index. Statistics and Probability Letters, 76(9), 920-930. [More Information]
  • Mueller, S., Husler, J. (2005). Iterative Estimation of the Extreme Value Index. Methodology and Computing in Applied Probability, 7(2), 139-148. [More Information]
  • Mueller, S., Welsh, A. (2005). Outlier Robust Model Selection in Linear Regression. Journal of the American Statistical Association, 100(472), 1297-1310. [More Information]
  • Mueller, S. (2005). Two-Stage Support Estimation. Australian and New Zealand Journal of Statistics, 47(4), 463-472. [More Information]
  • Karoussis, I., Mueller, S., Salvi, G., Heitz-Mayfield, L., Braegger, U., Lang, N. (2004). Association Between Periodontal and Peri-Implant Conditions: a 10-Year Prospective Study. Clinical Oral Implants Research, 15(1), 1-7. [More Information]
  • Mueller, S. (2003). Tail Estimation Based on Numbers of Near m-Extremes. Methodology and Computing in Applied Probability, 5(2), 197-210.
  • Borner, M., Dietrich, D., Stupp, R., Morant, R., Honegger, H., Wernli, M., Herrmann, R., Pestalozzi, B., Saletti, P., Hanselmann, S., Mueller, S., et al (2002). Phase II Study of Capecitabine and Oxaliplatin in First and Second-Line Treatment of Advanced or Metastatic Colorectal Cancer. Journal of Clinical Oncology, 20(7), 1759-1766.
  • Wittwer, M., Fluck, M., Hoppeler, H., Mueller, S., Desplanches, D., Billeter, R. (2002). Prolonged Unloading of Rat Soleus Muscle Causes Distinct Adaptations of the Gene Profile. The F A S E B Journal, 16(8 (June)), 884-886.
  • Glaus, A., Mueller, S. (2001). Messung derMudigkeit bei Krebskranken im Deutschen Sprachraum: Die Entwicklung des Fatigue Assessment Questionnaires. Pflege: die wissenschaftliche Zeitschrift fuer Pflegeberufe, 14(3), 161-170.
  • Aeberli, D., Mueller, S., Scmutz, R., Schmid, H. (2001). Predictive Value of Radiological Criteria for Disintegration Rates of Extracorporeal Shock Wave Lithotripsy. Urologia Internationalis, 66, 127-130.

Conferences

  • Mueller, S., Welsh, A. (2005). Robust Model Selection in Linear Regression Models. 55th session of the international statistical institute.
  • Mueller, S. (2003). Iterated Tail Index Estimation. Bulletin of the International Statistical Institute 54th Session.

Report

  • Mueller, S., Rufibach, K. (2006). Smooth tail index estimation.
  • Mueller, S., Rufibach, K. (2006). Smoothed Semi-Parametric Tail Index Estimation.
  • Mueller, S. (2005). A Comparison of human and pseudo-uniform random numbers.
  • Mueller, S., Vial, C. (2005). Partially Linear Model Selection.
  • Assoulin, D., Dietrich, D., Mueller, S., Schaller, M. (2001). Der Grundwasserspiegel und seine Abhangigkeit vom Niederschlag.
  • Mueller, S., Husler, J. (2001). Schlussbericht Betriebszählung 1995.

Other

  • Rufibach, K., Mueller, S. (2006), smoothtail: Smooth estimation of GPD shape parameter.

2017

  • Mueller, S., Boente, G., Croux, C., Romo, J., Van Elst, S. (2017). 2nd special issue on robust analysis of complex data. Computational Statistics and Data Analysis, 113, 395-397. [More Information]
  • Patrick, E., Schramm, S., Ormerod, J., Scolyer, R., Mann, G., Mueller, S., Yang, J. (2017). A multi-step classifier addressing cohort heterogeneity improves performance of prognostic biomarkers in three cancer types. Oncotarget, 8(2), 2807-2815. [More Information]
  • Hui, F., Mueller, S., Welsh, A. (2017). Hierarchical selection of fixed and random effects in generalized linear mixed models. Statistica Sinica, 27(2), 501-518. [More Information]

2016

  • Garcia, T., Mueller, S. (2016). Cox regression with exclusion frequency-based weights to identify neuroimaging markers relevant to Huntington's disease onset. Annals of Applied Statistics, 10(4), 2130-2156. [More Information]
  • Murray, K., Mueller, S., Turlach, B. (2016). Fast and flexible methods for monotone polynomial fitting. Journal of Statistical Computation and Simulation, 86(15), 2946-2966. [More Information]
  • Jayawardana, K., Schramm, S., Tembe, V., Mueller, S., Thompson, J., Scolyer, R., Mann, G., Yang, J. (2016). Identification, Review, and Systematic Cross-Validation of microRNA Prognostic Signatures in Metastatic Melanoma. Journal of Investigative Dermatology, 136(1), 245-254. [More Information]
  • You, C., Mueller, S., Ormerod, J. (2016). On generalized degrees of freedom with application in linear mixed models selection. Statistics and Computing, 26(1), 199-210. [More Information]
  • Tarr, G., Mueller, S., Weber, N. (2016). Robust estimation of precision matrices under cellwise contamination. Computational Statistics and Data Analysis, 93, 404-420. [More Information]

2015

  • Kaser, S., Froelicher, J., Li, Q., Muller, S., Metzger, U., Castiglione-Gertsch, M., Laffer, U., Maurer, C. (2015). Adenocarcinomas of the upper third of the rectum and the rectosigmoid junction seem to have similar prognosis as colon cancers even without radiotherapy, SAKK 40/87. Langenbecks Archives of Surgery, 400, 675-682. [More Information]
  • Jayawardana, K., Schramm, S., Haydu, L., Thompson, J., Scolyer, R., Mann, G., Mueller, S., Yang, J. (2015). Determination of prognosis in metastatic melanoma through integration of clinico-pathologic, mutation, mRNA, microRNA, and protein information. International Journal of Cancer, 136(4), 863-874. [More Information]
  • Patrick, E., Buckley, M., Mueller, S., Lin, D., Yang, J. (2015). Inferring data-specific micro-RNA function through the joint ranking of micro-RNA and pathways from matched micro-RNA and gene expression data. Bioinformatics, 31(17), 2822-2828. [More Information]
  • Mueller, S., Tarr, G. (2015). Much more than U-statistics: A symposium to celebrate Neville C. Weber. Statistical Society of Australia. Newsletter, 151, 10-12.
  • Tarr, G., Weber, N., Mueller, S. (2015). The difference of symmetric quantiles under long range dependence. Statistics and Probability Letters, 98, 144-150. [More Information]

2014

  • Garcia, T., Mueller, S., Carroll, R., Walzem, R. (2014). Identification of important regressor groups, subgroups and individuals via regularization methods: application to gut microbiome data. Bioinformatics, 30(6), 831-837. [More Information]
  • Garcia, T., Mueller, S. (2014). Influence of Measures of Significance based Weights in the Weighted Lasso. Journal of the Indian Society of Agricultural Statistics, 68(2), 131-144.
  • You, C., Ormerod, J., Mueller, S. (2014). On Variational Bayes Estimation and Variational Bayes Information Criteria for Linear Regression Models. Australian and New Zealand Journal of Statistics, 56(1), 73-87. [More Information]

2013

  • Oates, J., Casikar, I., Campain, A., Mueller, S., Yang, J., Reid, S., Condous, G. (2013). A prediction model for viability at the end of the first trimester after a single early pregnancy evaluation. Australian and New Zealand Journal of Obstetrics and Gynaecology, 53(1), 51-57. [More Information]
  • Sampson, J., Chatterjee, N., Carroll, R., Mueller, S. (2013). Controlling the local false discovery rate in the adaptive Lasso. Biostatistics, 14(4), 653-666. [More Information]
  • Murray, K., Heritier, S., Mueller, S. (2013). Graphical tools for model selection in generalized linear models. Statistics in Medicine, 32, 4438-4451. [More Information]
  • Mueller, S., Scealy, J., Welsh, A. (2013). Model selection in linear mixed models. Statistical Science, 28(2), 135-167. [More Information]
  • Murray, K., Mueller, S., Turlach, B. (2013). Revisiting fitting monotone polynomials to data. Computational Statistics, 28(5), 1989-2005. [More Information]
  • Garcia, T., Mueller, S., Carroll, R., Dunn, T., Thomas, A., Adams, S., Pillai, S., Walzem, R. (2013). Structured variable selection with q-values. Biostatistics, 14(4), 695-707. [More Information]

2012

  • Tarr, G., Mueller, S., Weber, N. (2012). A robust scale estimator based on pairwise means. Journal of Nonparametric Statistics, 24(1), 187-199. [More Information]
  • Feher, K., Whelan, J., Mueller, S. (2012). Exploring Multicollinearity Using a Random Matrix Theory Approach. Statistical Applications in Genetics and Molecular Biology, 11(3), A15-1-A15-33. [More Information]
  • Firmin, L., Mueller, S., Rosler, K. (2012). The latency distribution of motor evoked potentials in patients with multiple sclerosis. Clinical Neurophysiology, 123(12), 2414-2421. [More Information]

2011

  • Firmin, L., Mueller, S., Rosler, K. (2011). A method to measure the distribution of latencies of motor evoked potentials in man. Clinical Neurophysiology, 122, 176-182. [More Information]
  • Feher, K., Whelan, J., Mueller, S. (2011). Assessing modularity using a random matrix theory approach. Statistical Applications in Genetics and Molecular Biology, 10(1), 1-34. [More Information]
  • Martinez, J., Carroll, R., Mueller, S., Sampson, J., Chatterjee, N. (2011). Empirical Performance of Cross-Validation With Oracle Methods in a Genomics Context. The American Statistician, 65(4), 223-228. [More Information]
  • Mueller, S., Chhay, H. (2011). Partially smooth tail-index estimation for small samples. Computational Statistics, 26(3), 491-505. [More Information]
  • Tuft, K., Crowther, M., Connell, K., Mueller, S., McArthur, C. (2011). Predation risk and competitive interactions affect foraging of an endangered refuge-dependent herbivore. Animal Conservation: the rapid publication journal for quantitative studies in conservation, 14(4), 447-457. [More Information]

2010

  • Martinez, J., Carroll, R., Mueller, S., Sampson, J., Chatterjee, N. (2010). A note on the effect on power of score tests via dimension reduction by penalized regression under the null. The International Journal of Biostatistics, 6(1), A12-1-A12-12. [More Information]
  • Mueller, S., Welsh, A. (2010). On model selection curves. International Statistical Review, 78(2), 240-256. [More Information]

2009

  • Mueller, S., Vial, C. (2009). Partially linear model selection by the Bootstrap. Australian and New Zealand Journal of Statistics, 51(2), 183-200. [More Information]
  • Mueller, S., Welsh, A. (2009). Robust model selection in generalized linear models. Statistica Sinica, 19(3), 1155-1170. [More Information]
  • Mueller, S., Welsh, A. (2009). Robust model selection in generalized linear models (supplementary material). Statistica Sinica, 19(3), 1-5.
  • Mueller, S., Rufibach, K. (2009). Smooth tail-index estimation. Journal of Statistical Computation and Simulation, 79(9), 1155-1167. [More Information]

2008

  • Mueller, S., Rufibach, K. (2008). On the max-domain of attraction of distributions with log-concave densities. Statistics and Probability Letters, 78, 1440-1444. [More Information]

2006

  • Mueller, S., Conforto, A., Z’Graggen, W., Kaelin-Lang, A. (2006). Estimating the Number of Motor Units Using Random Sums with Independently Thinned Terms. Mathematical Biosciences, 202(1), 29-41. [More Information]
  • Mueller, S., Rufibach, K. (2006). Smooth tail index estimation.
  • Mueller, S., Rufibach, K. (2006). Smoothed Semi-Parametric Tail Index Estimation.
  • Rufibach, K., Mueller, S. (2006), smoothtail: Smooth estimation of GPD shape parameter.
  • Husler, J., Li, D., Mueller, S. (2006). Weighted Least Squares Estimation of the Extreme Value Index. Statistics and Probability Letters, 76(9), 920-930. [More Information]

2005

  • Mueller, S. (2005). A Comparison of human and pseudo-uniform random numbers.
  • Mueller, S., Husler, J. (2005). Iterative Estimation of the Extreme Value Index. Methodology and Computing in Applied Probability, 7(2), 139-148. [More Information]
  • Mueller, S., Welsh, A. (2005). Outlier Robust Model Selection in Linear Regression. Journal of the American Statistical Association, 100(472), 1297-1310. [More Information]
  • Mueller, S., Vial, C. (2005). Partially Linear Model Selection.
  • Mueller, S., Welsh, A. (2005). Robust Model Selection in Linear Regression Models. 55th session of the international statistical institute.
  • Mueller, S. (2005). Two-Stage Support Estimation. Australian and New Zealand Journal of Statistics, 47(4), 463-472. [More Information]

2004

  • Karoussis, I., Mueller, S., Salvi, G., Heitz-Mayfield, L., Braegger, U., Lang, N. (2004). Association Between Periodontal and Peri-Implant Conditions: a 10-Year Prospective Study. Clinical Oral Implants Research, 15(1), 1-7. [More Information]

2003

  • Mueller, S. (2003). Iterated Tail Index Estimation. Bulletin of the International Statistical Institute 54th Session.
  • Mueller, S. (2003). Tail Estimation Based on Numbers of Near m-Extremes. Methodology and Computing in Applied Probability, 5(2), 197-210.

2002

  • Borner, M., Dietrich, D., Stupp, R., Morant, R., Honegger, H., Wernli, M., Herrmann, R., Pestalozzi, B., Saletti, P., Hanselmann, S., Mueller, S., et al (2002). Phase II Study of Capecitabine and Oxaliplatin in First and Second-Line Treatment of Advanced or Metastatic Colorectal Cancer. Journal of Clinical Oncology, 20(7), 1759-1766.
  • Wittwer, M., Fluck, M., Hoppeler, H., Mueller, S., Desplanches, D., Billeter, R. (2002). Prolonged Unloading of Rat Soleus Muscle Causes Distinct Adaptations of the Gene Profile. The F A S E B Journal, 16(8 (June)), 884-886.

2001

  • Assoulin, D., Dietrich, D., Mueller, S., Schaller, M. (2001). Der Grundwasserspiegel und seine Abhangigkeit vom Niederschlag.
  • Glaus, A., Mueller, S. (2001). Messung derMudigkeit bei Krebskranken im Deutschen Sprachraum: Die Entwicklung des Fatigue Assessment Questionnaires. Pflege: die wissenschaftliche Zeitschrift fuer Pflegeberufe, 14(3), 161-170.
  • Aeberli, D., Mueller, S., Scmutz, R., Schmid, H. (2001). Predictive Value of Radiological Criteria for Disintegration Rates of Extracorporeal Shock Wave Lithotripsy. Urologia Internationalis, 66, 127-130.
  • Mueller, S., Husler, J. (2001). Schlussbericht Betriebszählung 1995.

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