تحليل العوامل المتنافسة في سرطان الثدي باستخدام نموذج المتعدد الحالات

Ibe, O. (2013). Markov processes for stochastic modeling. Newnes. DOI: https://doi.org/10.1016/B978-0-12-407795-9.00015-3

Ibe, O. (2014) Fundamentals of applied probability and random processes.Academic Press. DOI: https://doi.org/10.1016/B978-0-12-800852-2.00012-2

Journal Papers:

Andersen, P. K., Hansen, L. S., & Keiding, N. (1991). Non-and semi-parametric estimation of transition probabilities from censored observation of a non-homogeneous Markov process. Scandinavian Journal of Statistics.

Broët, P., de la Rochefordière, A., Scholl, S. M., Fourquet, A., De Rycke, Y., Pouillart, P., ... & Asselain, B. (1999). Analyzing prognostic factors in breast cancer using a multistate model. Breast cancer research and treatment. DOI: https://doi.org/10.1023/A:1006197524405

Bradburn, M. J., Clark, T. G., Love, S. B., & Altman, D. G. (2003). Survival analysis part II: multivariate data analysis–an introduction to concepts and methods. British journal of cancer. DOI: https://doi.org/10.1038/sj.bjc.6601119

Doutani, H., Doutani, J., Parveen, S., Khan, F., Baloch, D. M., & Roohullah, H. K. N. A. (2012). Clinical and histopathological characteristics of breast cancer in people of baluchistan and adjoining territory of afghanistan. Current Research Journal of Biological Sciences.‏

De Bock, G. H., Putter, H., Bonnema, J., Van Der Hage, J. A., Bartelink, H., & Van De Velde, C. J. (2009). The impact of loco-regional recurrences on metastatic progression in early-stage breast cancer: a multistate model. Breast cancer research and treatment. DOI: https://doi.org/10.1007/s10549-008-0300-2

de Wreede, L. C., Fiocco, M., & Putter, H. (2011). mstate: an R package for the analysis of competing risks and multi-state models. Journal of statistical software. DOI: https://doi.org/10.18637/jss.v038.i07

Grover, G., Swain, P. K., Goel, K., & Singh, V. (2018). Multistate Markov Modelling for Disease Progression of Breast Cancer Patients Based on CA15-3 Marker. Thailand Statistician.

Kay, R. (1982). The analysis of transition times in multistate stochastic processes using proportional hazard regression models. Communications in Statistics-Theory and Methods. DOI: https://doi.org/10.1080/03610928208828346

Meira-Machado, L., de Uña-Álvarez, J., Cadarso-Suarez, C., & Andersen, P. K. (2009). Multi-state models for the analysis of time-to-event data. Statistical methods in medical research. DOI: https://doi.org/10.1177/0962280208092301

Putter, H., van der Hage, J., de Bock, G. H., Elgalta, R., & van de Velde, C. J. (2006). Estimation and prediction in a multi‐state model for breast cancer. Biometrical Journal: Journal of Mathematical Methods in Biosciences. DOI: https://doi.org/10.1002/bimj.200510218

Saint-Pierre, P., Combescure, C., Daures, J.P., Godard, P., (2003).The analysis of asthma control under a markov assumption with use of covariates. Statistics in Medicine. DOI: https://doi.org/10.1002/sim.1680

Websites:

Annual Report Iraqi Cancer Registry (2015-2016).Republic of Health Ministry of HealthEnvironment. Iraqi Cancer Board.