The Factor analysis summarizes many variables by few factors and helps to understand the structure of a correlation matrix. It accounts for multi-collinearity among a large number of interrelated independent quantitative variables by grouping the variables into a few factors and reduces correlations.
In our case, we have countries as the units of observations. We have data on different aspects of these countries like population, density, percentage of people living in cities, religion, life expectancy, literacy rates, daily calorie intake, number of people affected from aids, fertility, death rates etc. Now, for the purpose of this lab we are taking LIFEXPF (Female Life Expectancy) as a dependent variable and running regression on that. However, before doing that we are running a factor analysis on other independent variables and grouping them into few factors and use these factor scores as independent variables for regression. This will help in reducing correlations among independent variables present in the model. The outputs from factor analysis are analyzed below in different sections followed by interpretation of the regression analysis.
1) The suitability of the data set for factor analysis (mention the correlation matrix & Bartlett's)
Here, I want to explain more about the data set I am using for factor analysis. The data set has a lot of missing information for independent as well as dependent variable. Thus, I exclude all the observations with missing cases to improve the analysis and the model.
First of all, I ran correlation matrix for all the independent variables to examine their strength of the relationship with the dependent variable LIFEXPF. From the correlation matrix, I find that variables like Population in thousand, No. of people per square km, region or economic group, aids cases, log base 10 of aids, log base 10 of population, predominant climate's correlation with LIFEXPF are not significant. Since they are not significantly correlated I exclude these variables from my model.
Said, H., Badru, B. B., & Shahid, M. (2011). Confirmatory Factor Analysis (CFA) for Testing Validity And Reliability Instrument in the Study of Education. Australian Journal of Basic and Applied Sciences, 5(12), 1098-1103. Retrieved April 24, 2014.
Applied Neuropsychology: Adult, 21(2), 1-8. Paunonen, S., & Ashton, M. (2001). Big five factors and facets and the prediction of behavior. Journal of Personality and Social Psychology, 81(1), 524-539. Pittenger, D. (2005).
As what was articulated in question #1, factors are describing words and letters. There is no possibility of average in this scenario because the grades are not in numbers. So it is a factor and cannot be calculated as we do to
Regression analysis is also used to understand which among the independent variables are related to the dependent variable, and to explore the forms of these relationships. In restricted circumstances, regression analysis can be used to infer causal relationships between the independent and dependent variables. However this can lead to illusions or false relationships, so caution is advisable;[2] for example, correlation does not imply
Some internal factors considered to be important in psychological aspects. Like knowledge about risk factors and risk reduction, attitudes, beliefs, social and life adaptation skills.
five factor theory is a fairly recent proposal and has its basis in earlier work,
A correlational method measure relationship between two or more variables: independent variable(s) and dependent variable. The independent variables are the experimental factors that the researcher can manipulate, while dependent variables are the things that the experimenter no control over, that include the outcome of the experiment (Class notes). The experimental method explores cause and effect of the study (David G. Myers, 2008).
Eysenck used mathematical steps in his research. In factor analysis, the experimenter begins making specific observations of a large number of people. The information is then quantified by calculating the correlation coefficient between the variables of the experiment. The number will depend on the amount of people who participate in the study. The mathematical deductive process continues until the figures are broken down into smaller, more basic dimensions called traits existing within the factors that represent a large group of closely related variables (Feist & Feist, 2009).
The primary factor of social boldness was low, which would explain why the client ranks his social life last behind school and work because he may not value social interactions as much. The primary factor of privateness being high helps support the reason why the client ranks his social life last behind school and work because he may tend to keep to himself and prefer not to open up to others. The primary factor of liveliness is high and that may explain why even though social interactions are ranked low, it is still important enough for the client to come to counseling to address his
An organizational analysis is an important tool to become familiar with how medical businesses and organizations are able to meet standards of care, provide services for the community and provide employment to health care providers. There are many different aspects to evaluate in an organizational analysis. This paper will describe these many aspects and apply the categories to the University Medical Center (UMC) as the organization being analyzed.
Although the Fama and French three-factor model operates slightly better than CAPM, it does not indicate that CAPM is impractical to use (Hibbert and Lawrence 2010).
Psychologist Lewis R. Goldberg reviewed the model and came up with the theory that the five factors are terms that over a long period of time, the human race has collectively narrowed down and use universally to describe an individuals personality. It gives individuals a sense of... ... middle of paper ... ...to psychology and outside of psychology is also a convincing argument for the support of the model. Bibliography DAVEY. G. (2004).
Wickens, C. D., Lee, J. D., Liu, Y., & Becker, S. E. (2004). An introduction to human Factors Enginnering. (L. Jewell, Ed.)Wickens Christopher D Lee John D Liu Yili Becker Sallie E Gordon (pp. 120-183). Pearson Education,Inc.
Trait and Factor Theories. The basis of trait and factor theories is the assumption that there are unique traits that can be reliably measured and that it is possible to match individual traits to occupational requirements. Holland identified six types of occupations theorized that people seek work environments and occupations that match their preferred traits. However, some people question the accuracy of the instruments used to measure...
As we can see, the unmeasurable factors are mostly about social consciousness, culture and a higher level of development stages. Most developing countries are still struggling in the first stage to balance development, environmental quality and living quality.