A competing risks situation arises when a unit can fail due to several distinct failure types. In a competing risk situation, standard techniques from survival analysis may lead to incorrect and biased results. In this thesis, the theory of competing risks is used to identify possible risk factors for breast, uterine and ovarian cancer. This has been done by regression on the cause specific hazard functions, the subdistribution hazard functions and two approximate methods. Cox regression is used for a complete analysis of the medical data.By following 61457 women over approximately 50 years, it has been observed 3407 cases of breast cancer, 934 of uterine cancer and 843 of ovarian cancer. Summarized, it has been found that several births decrease the risk of breast, uterine and ovarian cancer. Obesity is associated with increasing risk of ovarian cancer for postmenopausal women, but not premenopausal. A long reproductive period (early menarche and/or late menopause) and high BMI increases the risk of breast and uterine cancer. Late first and last birth decreases the risk of uterine cancer, while it increases the risk of breast cancer. The data used in the analysis is selected from a screening program organized by the Norwegian Cancer Society for early diagnosis of breast cancer. postmenopausale women, but not premenopausale. A long reproductive period (early menarche and/or late menopause) and high BMI increases the risk of breast and uterine cancer. Late first and last birth decreases the risk of uterine cancer, while it increases the risk of breast cancer. The data used in the analysis is selected from a screening program organized by the Norwegian Cancer Society for early diagnosis of breast cancer.