Regression-Discontinuity Design. A powerful, alternative design for causal inference that is underutilized in the health and intervention sciences is the regression discontinuity (RD) design (Thistlewaite & Campbell, 1960). In its simplest form, the RD design involves the use of a screening measure of some form that is continuous and given to all persons. A cut point or criterion is set, which determines whether individuals are assigned to an intervention condition or a comparison condition. The…
3.3 Hypothesis H1: The relationship between total debt to total capital and firm value is significantly positive. According to most trade-off theory, because of less expensive cost of debt than cost of equity and tax benefits of debt, usage of debt financing increase corporate value. Meanwhile, according to agency theory, debt financing introduces creditor protection provisions which limit discretionary cash flow of managers, supervise managers’ behaviors against waste of corporate resources…
In the 1940s, Raymond Cattell was able to take Allport’s 4000 traits and boil it down through factor analysis. Factor analysis refers to the mathematical consolidation of commonly appearing variables and the summarising of correlating data. He used factor analysis to eliminate synonyms and the very rare or unused traits (Friedman & Schustack, 2014). Cattell was able to reduce the list of traits from over 4000 to 16 personality variables. This reduction in personality variables was attributed to…
Without technology Project Based Learning will not be as effective as it is today. PBL relies on collaboration, real-world connection, critical thinking and authentic assessments – components that are best served with technology. The key is to rearrange the way instructions have been presented where students’ experiences are used to teach abstract Math concepts. A PBL design starts with real world contexts, to conceptual understanding, then back to application and then creation. Project is…
relationship between the variables of interest. This can be described in numerous ways; this also depends on the analysis. This is concerned with how each variable is related to other similar variables. This association is based on the strength of the linear relationship in the degree of monotonicity. To the degree that it is based on counting various pairs in a relationship. Known as a statistical tool that investigates relationships among variables, regression analysis seeks to determine the…
Introduction What is innovation? A using of new ideas to products, processes and other aspects of a firm activities lead to an increasing in value of the firm, benefits to customers or other enterprise, this situation is called innovation. A key issue to distinguish innovation, bringing a truly novel item that is produced by new techniques and designs into market; this item can be new to the firm, new to relevant market. Moreover, whether relevant market is domestic or global market is based…
Throughout the Bronze Age, the cultures of the Aegean civilizations showed influences in trade, religion and economic administration. The iconography of these civilizations not only revealed their culture but also how they functioned throughout Greece. Weapons and animal representations like bulls and griffins, are all characteristic of Minoan and Mycenaean civilizations. But the settings in which they are presented offer deeper implications into their values and identity. Excavated frescos,…
intervention is small and not clinically significant. Association and causality is not proven in this case. The data set given was imported to Stata and summary statistics were used and graphs and scatter plots on Stata to visualise and analyse the data. 3 A linear regression analysis was done with Stata to find the treatment effect to adjust for baseline co variates. (propensity score matching) The results are as below- weight after treatment being the dependent variable (continuous…
Performance Evaluation In order to assess the model accuracy, it is necessary to use some quantitative measures of learning. In this study the Mean Squared Error (MSE) and regression analysis were used to evaluate the model performance. MSE is a useful measure of success for numeric prediction and is calculated using Eq. (1). It is worth mentioning that small values of MSE indicate better performance of the ANN model. It was found that the optimum performance of the model is at 25 neurons with…
From there I can add a regression line, find the equation of my model and the correlation coefficient. This will indicate how strong a relationship there is between my two variables. I can also use my data to plot a residual plot to prove that a linear model is a good fit for my data.…