Formation of Exchange Rates on the Russian Market: Dynamics and Modelling

Galina Kovaleva. The Formation of the Exchange Rate on the Russian Market: Dynamics and Modelling. The Russian financial market is fast becoming one of the major sectors of the Russian economy. Assets have been increasing steadily, while new market segments and new financial market instruments have emerged. Kovaleva attempted to isolate the factors influencing exchange rates, determine patterns in the dynamic changes to the rouble/dollar exchange rate, construct models of the processes, and on the basis of these activities make forecasts. She studied the significance of economic indicators influencing the rouble/dollar exchange rate at different times, and developed multi-factor econometric models. In order to reveal the inner structure of the financial indicators and to work out ex-post forecasts for different time intervals, she carried out a series of calculations with the aim of constructing trend-cyclical (TC) and harmonic models, and Box and Jenkins models. She found that: 1. The Russian financial market is dependant on the rouble/dollar exchange rate. Its dynamics are formed under the influence of the short-term state treasury notes and government bonds markets, interbank loans, the rouble/DM exchange rate, the inflation rate, and the DM/dollar exchange rate. The exchange rate is influenced by sales on the Moscow Interbank Currency Exchange and the mechanism of those sales. 2. The TC model makes it possible to conduct an in-depth study of the structure of the processes and to make forecasts of the dynamic changes to currency indicators. 3. The Russian market is increasingly influenced by the world currency market and its prospects are of crucial interest for the world financial community.

Rates of disease progression according to initial highly active antiretroviral therapy regimen: a collaborative analysis of 12 prospective cohort studies

BACKGROUND: No large clinical end-point trials have been conducted comparing regimens among human immunodeficiency virus type 1-positive persons starting antiretroviral therapy. We examined clinical progression according to initial regimen in the Antiretroviral Therapy Cohort Collaboration, which is based on 12 European and North American cohort studies. METHODS: We analyzed progression to death from any cause and to AIDS or death (AIDS/death), comparing efavirenz (EFV), nevirapine (NVP), nelfinavir, idinavir, ritonavir (RTV), RTV-boosted protease inhibitors (PIs), saquinavir, and abacavir. We also compared nucleoside reverse-transcriptase inhibitor pairs: zidovudine/lamivudine (AZT/3TC), stavudine (D4T)/3TC, D4T/didanosine (DDI), and others. RESULTS: A total of 17,666 treatment-naive patients, 55,622 person-years at risk, 1,617 new AIDS events, and 895 deaths were analyzed. Compared with EFV, the adjusted hazard ratio (HR) for AIDS/death was 1.28 (95% confidence interval [CI], 1.03-1.60) for NVP, 1.31 (95% CI, 1.01-1.71) for RTV, and 1.45 (95% CI, 1.15-1.81) for RTV-boosted PIs. For death, the adjusted HR for NVP was 1.65 (95% CI, 1.16-2.36). The adjusted HR for death for D4T/3TC was 1.35 (95% CI, 1.14-1.59), compared with AZT/3TC. CONCLUSIONS: Outcomes may vary across initial regimens. Results are observational and may have been affected by bias due to unmeasured or residual confounding. There is a need for large, randomized, clinical end-point trials.

Estimating Multiple Tumor Transition Rates Based on Data from Survival/Sacrifice Experiments

In this paper, we focus on the model for two types of tumors. Tumor development can be described by four types of death rates and four tumor transition rates. We present a general semi-parametric model to estimate the tumor transition rates based on data from survival/sacrifice experiments. In the model, we make a proportional assumption of tumor transition rates on a common parametric function but no assumption of the death rates from any states. We derived the likelihood function of the data observed in such an experiment, and an EM algorithm that simplified estimating procedures. This article extends work on semi-parametric models for one type of tumor (see Portier and Dinse and Dinse) to two types of tumors.

Gauss-Seidel Estimation of Generalized Linear Mixed Models with Application to Poisson Modeling of Spatially Varying Disease Rates

Generalized linear mixed models (GLMMs) provide an elegant framework for the analysis of correlated data. Due to the non-closed form of the likelihood, GLMMs are often fit by computational procedures like penalized quasi-likelihood (PQL). Special cases of these models are generalized linear models (GLMs), which are often fit using algorithms like iterative weighted least squares (IWLS). High computational costs and memory space constraints often make it difficult to apply these iterative procedures to data sets with very large number of cases. This paper proposes a computationally efficient strategy based on the Gauss-Seidel algorithm that iteratively fits sub-models of the GLMM to subsetted versions of the data. Additional gains in efficiency are achieved for Poisson models, commonly used in disease mapping problems, because of their special collapsibility property which allows data reduction through summaries. Convergence of the proposed iterative procedure is guaranteed for canonical link functions. The strategy is applied to investigate the relationship between ischemic heart disease, socioeconomic status and age/gender category in New South Wales, Australia, based on outcome data consisting of approximately 33 million records. A simulation study demonstrates the algorithm's reliability in analyzing a data set with 12 million records for a (non-collapsible) logistic regression model.

A systematic review of the survival and complication rates of resin-bonded bridges after an observation period of at least 5 years

OBJECTIVES: The objectives of this systematic review were to assess the 5-year survival of resin-bonded bridges (RBBs) and to describe the incidence of technical and biological complications. METHODS: An electronic Medline search complemented by manual searching was conducted to identify prospective and retrospective cohort studies on RBBs with a mean follow-up time of at least 5 years. Patients had to have been examined clinically at the follow-up visit. Assessment of the identified studies and data extraction were performed independently by two reviewers. Failure and complication rates were analyzed using random-effects Poissons regression models to obtain summary estimates of 5-year proportions. RESULTS: The search provided 6110 titles and 214 abstracts. Full-text analysis was performed for 93 articles, resulting in 17 studies that met the inclusion criteria. Meta-analysis of these studies indicated an estimated survival of RBBs of 87.7% (95% confidence interval (CI): 81.6-91.9%) after 5 years. The most frequent complication was debonding (loss of retention), which occurred in 19.2% (95% CI: 13.8-26.3%) of RBBs over an observation period of 5 years. The annual debonding rate for RBBs placed on posterior teeth (5.03%) tended to be higher than that for anterior-placed RBBs (3.05%). This difference, however, did not reach statistical significance (P=0.157). Biological complications, like caries on abutments and RBBs lost due to periodontitis, occurred in 1.5% of abutments and 2.1% of RBBs, respectively. CONCLUSION: Despite the high survival rate of RBBs, technical complications like debonding are frequent. This in turn means that a substantial amount of extra chair time may be needed following the incorporation of RBBs. There is thus an urgent need for studies with a follow-up time of 10 years or more, to evaluate the long-term outcomes.

A systematic review of the 5-year survival and complication rates of implant-supported single crowns

OBJECTIVES: The objective of this systematic review was to assess the 5-year survival of implant-supported single crowns (SCs) and to describe the incidence of biological and technical complications. METHODS: An electronic MEDLINE search complemented by manual searching was conducted to identify prospective and retrospective cohort studies on SCs with a mean follow-up time of at least 5 years. Failure and complication rates were analyzed using random-effects Poisson's regression models to obtain summary estimates of 5-year proportions. RESULTS: Twenty-six studies from an initial yield of 3601 titles were finally selected and data were extracted. In a meta-analysis of these studies, survival of implants supporting SCs was 96.8% [95% confidence interval (CI): 95.9-97.6%] after 5 years. The survival rate of SCs supported by implants was 94.5% (95% CI: 92.5-95.9%) after 5 years of function. The survival rate of metal-ceramic crowns, 95.4% (95% CI: 93.6-96.7%), was significantly (P=0.005) higher than the survival rate, 91.2% (95% CI: 86.8-94.2%), of all-ceramic crowns. Peri-implantitis and soft tissue complications occurred adjacent to 9.7% of the SCs and 6.3% of the implants had bone loss exceeding 2 mm over the 5-year observation period. The cumulative incidence of implant fractures after 5 years was 0.14%. After 5 years, the cumulative incidence of screw or abutment loosening was 12.7% and 0.35% for screw or abutment fracture. For supra-structure-related complications, the cumulative incidence of ceramic or veneer fractures was 4.5%. CONCLUSION: It can be concluded that after an observation period of 5 years, high survival rates for implants and implant-supported SCs can be expected. However, biological and particularly technical complications are frequent.