A Nonparametric Method for Ascertaining Change Points in Regression Regimes

Of interest is the specific model called the joinpoint two regime regression or broken line model composed of one regression line and a horizontal ray. This is a very restricted but highly useful subset of the well-researched change point problem. The usual approach to a more general model was first presented by Quandt (1958) who found the maximum likelihood estimates of the slope, intercept and joinpoint by assuming that the error terms are generated under the usual assumptions, that is, from a normal distribution with constant variance and are uncorrelated. We develop a method that does not rely on this assumption, demonstrate its use on an example of proximity indexes of whale cow and calf pairs, and compare the new method to the Quandt estimates in a simulation study showing this new method performs adequately

Asymptotics and confidence estimation in segmented regression models.

Standard regularity assumptions for regression models are not satisfied in segmented regression models with an unknown change point, and consequently standard asymptotic results and inferential methods for confidence estimation are not applicable. This dissertation considers a clustered segmented regression model with a continuity constraint and considers estimators of the model parameters based on the likelihood principle. The strong consistency of the maximum likelihood estimators is established. To consider the asymptotic distribution, two cases must be considered. Case 1 occurs when the true change point occurs between two of the observation times, while Case 2 occurs when the true change point occurs at one of the observation times. In each case, the asymptotic distribution of relevant estimators is derived. These results are used to develop a new comprehensive algorithm for constructing a confidence interval for the change point parameter which works for both cases using all available data in determining the confidence bounds. This algorithm is compared to an existing method known as the removal algorithm. A slight modification to the comprehensive algorithm is also considered. Finally, these methods for obtaining confidence intervals are compared by simulation studies and applied to a real data set

Child health in an era of globalization : a case study of Saskatoon, Saskatchewan

Globalization is increasingly considered an important influence on the determinants of health. Globalization, for the purposes of this study, was defined as “a process of greater integration within the world economy through movements of goods and services, capital, technology and (to a lesser extent) labour, which lead increasingly to economic decisions being influenced by global conditions.”(1) Although there have been many conceptual and theoretical explorations of the globalization and health relationship, only a limited number of empirical studies have sought to link the processes of globalization to health effects in a specific context and/or for a particular population such as children. The objectives of this thesis were two-fold: to investigate primarily the economic pathways and related political pathways by which globalization influences the determinants of health and health outcomes in low-income children ages zero to five in a mid-sized Canadian city (Saskatoon, Saskatchewan); to identify and analyze the policy responses at various levels (national, provincial, and municipal) that address the effects of globalization on determinants of health such as household income and distribution, employment and education for parents, housing, and social programs. This study was a case study that used mixed methods. The case in this research was Saskatoon, a mid-size city located in the Canadian province of Saskatchewan. The analytical framework used to guide this study was developed by Labonte and Torgerson.(2) Methods included: a demographic profile for the City of Saskatoon; an environmental scan of federal, provincial, and municipal policy that has direct relevance for child health; process tracing; semi-structured interviews with low-income parents of young children (n=26); and trend analysis of child health outcomes among children ages zero to five. The current phase of globalization in Canada and Saskatchewan is inextricably linked with the implementation of neoliberal policies such as tax restructuring, trade liberalization, privatization, deregulation, and greater integration in the global economy. This phase of globalization contributed to changes in the determinants of health that affect children and their families in Saskatoon. For instance, globalization has involved retrenchment of the welfare state in Canada and Saskatchewan. As the welfare state diminished in size and responsibility, poverty tended to deepen among those that were already poor. The retrenchment of the welfare state also led to diminished program access. In addition, globalization has emphasized the restructuring of the labour market to be more competitive and flexible. A restructured labour market and reduced access to services and programs contributed to greater inequalities in income in Canada, Saskatchewan, and Saskatoon. Finally, globalization contributed to declining housing affordability in Canada’s cities such as Saskatoon. Trend analysis at the neighbourhood-level to determine the linkages between changes in the determinants of child health and changes in child health outcomes was inconclusive. Further research is required to determine if the disparities in the determinants of child health that have been exacerbated by the economic and political processes of globalization have contributed to increasing disparities in child health outcomes. This study indicated that the economic and political processes of globalization influenced the determinants of health among young low-income children and their families in Saskatoon through a number of pathways, but this is not to suggest that globalization was the only phenomenon at work. Although it was very difficult to draw any conclusions regarding the globalization and health relationship with certainty, this study offered a logical and a multi-prong approach to examining the effects of globalization on children’s health and health determining conditions. Studies of this nature are important for contributing to our understanding of the complex structures that influence health and for building up the linkages between globalization and health on a case-by-case basis

Hydrogeochemical seismic precursors: pilot study for future hydrogeochemical networks

The aim of this thesis is to illustrate the importance of establishing a method of investigation of seismic precursors based on the investigation of possible relationships between groundwater and earthquakes, through hydrogeological, hydrogeochemical and seismic monitoring of the territory under consideration. This will be done through a detailed and systematic study of hydrogeological and hydrogeochemical factors that can be potentially influenced by seismic activity, such as: piezometric levels, temperature, electrical conductivity, chemical composition of groundwater and dissolved gases in solution. The analysis of these factors will allow to verify the existence and the modalities of manifestation of a cause / effect relationship between the hydrogeological, hydrogeochemical and seismic signals. The objective of this PhD project is therefore the study of potential geochemical precursors that will allow the short-term forecast (from days to months) of seismic phenomena of medium-high magnitude (M ≥ 5.0) in order to initiate an effective preventive action. In particular, through this study, I want to highlight the importance of collecting data from a network of monitoring stations spread over a seismic territory and for a long time, with the construction of a national hydrogeochemical monitoring network. The advances in identifying the earthquakes hydrogeochemical precursors depends on the systematic and patient acquisition of long-term multiparametric data set. Long records are therefore essential to identify precursor signals of earthquake responses, especially in regions with abundant seismicity. Well-developed documentation is required to assess the uniqueness and statistical significance of possible precursor signals and to identify and screen out meteorological and seasonal signals. The solid statistical significance of the results therefore depends on the length of the time series, that is the observations of more than one seismic event and the multiparametric nature of the recorded data (Ingebritsen and Manga, 2014). The aim of this PhD project is therefore the better understanding of seismic precursors of hydrogeochemical nature and the related processes to facilitate the understanding of site-specific phenomena and their possible applicability to other sites or their general and global value

Change-point Problem and Regression: An Annotated Bibliography

The problems of identifying changes at unknown times and of estimating the location of changes in stochastic processes are referred to as the change-point problem or, in the Eastern literature, as disorder . The change-point problem, first introduced in the quality control context, has since developed into a fundamental problem in the areas of statistical control theory, stationarity of a stochastic process, estimation of the current position of a time series, testing and estimation of change in the patterns of a regression model, and most recently in the comparison and matching of DNA sequences in microarray data analysis. Numerous methodological approaches have been implemented in examining change-point models. Maximum-likelihood estimation, Bayesian estimation, isotonic regression, piecewise regression, quasi-likelihood and non-parametric regression are among the methods which have been applied to resolving challenges in change-point problems. Grid-searching approaches have also been used to examine the change-point problem. Statistical analysis of change-point problems depends on the method of data collection. If the data collection is ongoing until some random time, then the appropriate statistical procedure is called sequential. If, however, a large finite set of data is collected with the purpose of determining if at least one change-point occurred, then this may be referred to as non-sequential. Not surprisingly, both the former and the latter have a rich literature with much of the earlier work focusing on sequential methods inspired by applications in quality control for industrial processes. In the regression literature, the change-point model is also referred to as two- or multiple-phase regression, switching regression, segmented regression, two-stage least squares (Shaban, 1980), or broken-line regression. The area of the change-point problem has been the subject of intensive research in the past half-century. The subject has evolved considerably and found applications in many different areas. It seems rather impossible to summarize all of the research carried out over the past 50 years on the change-point problem. We have therefore confined ourselves to those articles on change-point problems which pertain to regression. The important branch of sequential procedures in change-point problems has been left out entirely. We refer the readers to the seminal review papers by Lai (1995, 2001). The so called structural change models, which occupy a considerable portion of the research in the area of change-point, particularly among econometricians, have not been fully considered. We refer the reader to Perron (2005) for an updated review in this area. Articles on change-point in time series are considered only if the methodologies presented in the paper pertain to regression analysis

Associations Between Climate, Latitude, Fertility and the Decline of the US Sex Ratio at Birth

The US sex ratio at birth (SRB) has declined since 1970, while ambient temperatures have been increasing. This study examines the temporal and spatial variation of the US SRB from 1979–2002 in association with fertility rates and climate variables. Approximately 62.8 million birth records from the National Center for Health Statistics were linked to monthly climate division data and county level socioeconomic variables to evaluate the association of SRB and environmental conditions at or near the time of conception. Seasonal variation in US SRB is detectable in time series analysis, and is somewhat in phase with variation in fertility. Logistic regression analysis shows that temperature in the month before conception is significantly positively correlated with the likelihood of a male birth when birth order, maternal age, maternal education, plurality, gestation length, race, and Hispanic origin are controlled. This association was significant in models that include all births from 1979–1988, non-Hispanic white births from 1979–1988, and all births in US large counties from 1979–2002. Geographic nonstationarity of US SRB was found in smoothed rate climate division maps for 1979–1988, with higher SRB in latitudes below 40 degrees N, especially in the southeastern US. However, both the overall rates of summer conception and the likelihood of summer male conception are reduced in lower latitudes relative to higher ones. A logistic regression model was also fit using only non-Hispanic births from US large counties from 1989–2002. In addition to a significant positive association of sex ratio and temperature in the month before conception, deviation from normal monthly temperature during the month of conception, compared to the 1971–2000 baseline temperature, is significantly associated with sex ratio variation. In this population, fewer males were conceived when temperature extremes were significantly above normal; more males were conceived when temperatures were significantly below normal. In both high and low latitude zones over this period, the peak of male conceptions shifted to earlier in the year. Variation in SRB is potentially a sentinel health event and this research suggests that the association between temperature and SRB should be integral to any study of SRB variation across large geographic areas or long time periods