Univariate, bivariate, and multivariate methods in corpus-based lexicography : A study of synonymy

In this dissertation, I present an overall methodological framework for studying linguistic alternations, focusing specifically on lexical variation in denoting a single meaning, that is, synonymy. As the practical example, I employ the synonymous set of the four most common Finnish verbs denoting THINK, namely ajatella, miettiä, pohtia and harkita ‘think, reflect, ponder, consider’. As a continuation to previous work, I describe in considerable detail the extension of statistical methods from dichotomous linguistic settings (e.g., Gries 2003; Bresnan et al. 2007) to polytomous ones, that is, concerning more than two possible alternative outcomes. The applied statistical methods are arranged into a succession of stages with increasing complexity, proceeding from univariate via bivariate to multivariate techniques in the end. As the central multivariate method, I argue for the use of polytomous logistic regression and demonstrate its practical implementation to the studied phenomenon, thus extending the work by Bresnan et al. (2007), who applied simple (binary) logistic regression to a dichotomous structural alternation in English. The results of the various statistical analyses confirm that a wide range of contextual features across different categories are indeed associated with the use and selection of the selected think lexemes; however, a substantial part of these features are not exemplified in current Finnish lexicographical descriptions. The multivariate analysis results indicate that the semantic classifications of syntactic argument types are on the average the most distinctive feature category, followed by overall semantic characterizations of the verb chains, and then syntactic argument types alone, with morphological features pertaining to the verb chain and extra-linguistic features relegated to the last position. In terms of overall performance of the multivariate analysis and modeling, the prediction accuracy seems to reach a ceiling at a Recall rate of roughly two-thirds of the sentences in the research corpus. The analysis of these results suggests a limit to what can be explained and determined within the immediate sentential context and applying the conventional descriptive and analytical apparatus based on currently available linguistic theories and models. The results also support Bresnan’s (2007) and others’ (e.g., Bod et al. 2003) probabilistic view of the relationship between linguistic usage and the underlying linguistic system, in which only a minority of linguistic choices are categorical, given the known context – represented as a feature cluster – that can be analytically grasped and identified. Instead, most contexts exhibit degrees of variation as to their outcomes, resulting in proportionate choices over longer stretches of usage in texts or speech.

Variations in paediatric upper respiratory surgery rates within and between two Nordic countries

Lasten ylähengitystiekirurgia (kita-nielurisojen poisto ja tärykalvon putkitus) on länsimaissa erittäin yleistä. Leikkausten lukumäärät vaihtelevat niin kansallisesti kuin kansainvälisestikin, mutta selvää syytä näille eroille ei tiedetä. Hoitosuositusten merkitys käytäntöihin on kyseenalaistettu ja voi olla, ettei hoitosuosituksia noudateta. Leikkaukset saattavat aiheuttaa lapsipotilaille psykologisen vamman, ja lisäksi niihin sisältyy komplikaatioiden, jopa kuoleman, vaara. Jotta haittoja voidaan välttää, on tärkeää tunnistaa ne lapset, jotka hyötyvät leikkauksesta. Ongelma on paitsi lääketieteellinen, myös taloudellinen: ylähengitystiekirurgiasta aiheutuu merkittäviä kuluja. Leikkausmäärien arvioiminen on tärkeää, jotta leikkauskäytäntöjä voidaan järkeistää. Tässä väitöskirjatyössä tutkittiin ylähengitystieleikkausten määriä Suomessa ja Norjassa sekä näiden kahden maan välillä. Aiempaa tutkimusta aiheesta ei kummassakaan maassa ole tehty. Kitarisanpoiston, välikorvan putkituksen, tärykalvopiston, nielurisanpoiston ja kita- ja nielurisanpoiston leikkausmäärät saatiin kansallisista tietokannoista. Lukuja verrattiin ko. maan lasten lukumäärään, maantieteelliseen sijoittumiseen sekä lasten ikään ja sukupuoleen. Lisäksi leikkausmääriä arvioitiin suhteessa korva-, nenä- ja kurkkulääkäreiden sekä yleislääkäreiden määrään, maantieteelliseen sijoittumiseen ja lääkäreiden ikään ja sukupuoleen. Leikkausten määrissä havaittiin suurta vaihtelua niin Suomessa kuin Norjassa. Suomessa suurimmat erot leikkausmäärissä löydettiin läntisen ja itäisen miljoonapiirin välillä. Läntisessä piirissä tehtiin lähes kaksin kertaa enemmän leikkauksia kuin itäisessä piirissä. Norjassa suurimmat erot olivat pohjoisen ja itäisen piirin välillä. Pohjoisessa piirissä tehtiin kaksinkertainen määrä leikkauksia itäiseen piirrin verrattuna. Suomessa tehtiin tutkimuksen koko aikavälillä enemmän kitarisanpoistoja kuin Norjassa, mutta ko. leikkausten määrä oli maassamme selvästi laskussa. Vuonna 2002 Suomessa tehtiin 2,5 kertaa enemmän kitarisanpoistoja kuin Norjassa. (Kita)nielurisanpoistoja tehtiin kuitenkin Suomessa vähemmän kuin Norjassa. Näiden leikkausten määrät pysyivät tutkimuksen aikavälillä Suomessa samalla tasolla, kun Norjassa leikkausmäärät hieman nousivat. Suomalaisia lapsia leikattiin keskimäärin paljon nuorempina kuin norjalaisia lapsia. Tutkimuksessa ei löydetty selitystä ylähengitystieleikkausten määrän suurelle vaihtelulle Suomessa ja Norjassa tai maiden välillä. Kuitenkin Suomessa tehtyjen kitarisanpoistojen huomattavan vähenemisen myötä maiden ylähengitystieleikkausten määrät lähenivät toisiaan.

Studies on Binary Time Series Models with Applications to Empirical Macroeconomics and Finance

This thesis studies binary time series models and their applications in empirical macroeconomics and finance. In addition to previously suggested models, new dynamic extensions are proposed to the static probit model commonly used in the previous literature. In particular, we are interested in probit models with an autoregressive model structure. In Chapter 2, the main objective is to compare the predictive performance of the static and dynamic probit models in forecasting the U.S. and German business cycle recession periods. Financial variables, such as interest rates and stock market returns, are used as predictive variables. The empirical results suggest that the recession periods are predictable and dynamic probit models, especially models with the autoregressive structure, outperform the static model. Chapter 3 proposes a Lagrange Multiplier (LM) test for the usefulness of the autoregressive structure of the probit model. The finite sample properties of the LM test are considered with simulation experiments. Results indicate that the two alternative LM test statistics have reasonable size and power in large samples. In small samples, a parametric bootstrap method is suggested to obtain approximately correct size. In Chapter 4, the predictive power of dynamic probit models in predicting the direction of stock market returns are examined. The novel idea is to use recession forecast (see Chapter 2) as a predictor of the stock return sign. The evidence suggests that the signs of the U.S. excess stock returns over the risk-free return are predictable both in and out of sample. The new "error correction" probit model yields the best forecasts and it also outperforms other predictive models, such as ARMAX models, in terms of statistical and economic goodness-of-fit measures. Chapter 5 generalizes the analysis of univariate models considered in Chapters 2 4 to the case of a bivariate model. A new bivariate autoregressive probit model is applied to predict the current state of the U.S. business cycle and growth rate cycle periods. Evidence of predictability of both cycle indicators is obtained and the bivariate model is found to outperform the univariate models in terms of predictive power.

Carbon dynamics in peatlands under changing hydrology : Effects of water level drawdown on litter quality, microbial enzyme activities and litter decomposition rates

Pristine peatlands are carbon (C) accumulating wetland ecosystems sustained by a high water level (WL) and consequent anoxia that slows down decomposition. Persistent WL drawdown as a response to climate and/or land-use change directly affects decomposition: increased oxygenation stimulates decomposition of the old C (peat) sequestered under prior anoxic conditions. Responses of the new C (plant litter) in terms of quality, production and decomposability, and the consequences for the whole C cycle of peatlands are not fully understood. WL drawdown induces changes in plant community resulting in shift in dominance from Sphagnum and graminoids to shrubs and trees. There is increasing evidence that the indirect effects of WL drawdown via the changes in plant communities will have more impact on the ecosystem C cycling than any direct effects. The aim of this study is to disentangle the direct and indirect effects of WL drawdown on the new C by measuring the relative importance of 1) environmental parameters (WL depth, temperature, soil chemistry) and 2) plant community composition on litter production, microbial activity, litter decomposition rates and, consequently, on the C accumulation. This information is crucial for modelling C cycle under changing climate and/or land-use. The effects of WL drawdown were tested in a large-scale experiment with manipulated WL at two time scales and three nutrient regimes. Furthermore, the effect of climate on litter decomposability was tested along a north-south gradient. Additionally, a novel method for estimating litter chemical quality and decomposability was explored by combining Near infrared spectroscopy with multivariate modelling. WL drawdown had direct effects on litter quality, microbial community composition and activity and litter decomposition rates. However, the direct effects of WL drawdown were overruled by the indirect effects via changes in litter type composition and production. Short-term (years) responses to WL drawdown were small. In long-term (decades), dramatically increased litter inputs resulted in large accumulation of organic matter in spite of increased decomposition rates. Further, the quality of the accumulated matter greatly changed from that accumulated in pristine conditions. The response of a peatland ecosystem to persistent WL drawdown was more pronounced at sites with more nutrients. The study demonstrates that the shift in vegetation composition as a response to climate and/or land-use change is the main factor affecting peatland ecosystem C cycle and thus dynamic vegetation is a necessity in any models applied for estimating responses of C fluxes to changes in the environment. The time scale for vegetation changes caused by hydrological changes needs to extend to decades. This study provides grouping of litter types (plant species and part) into functional types based on their chemical quality and/or decomposability that the models could utilize. Further, the results clearly show a drop in soil temperature as a response to WL drawdown when an initially open peatland converts into a forest ecosystem, which has not yet been considered in the existing models.