Nowadays, internet-based surveys are increasingly used for data collection, because their usage is simple and cheap. Also they give fast access to a large group of respondents. There are many factors affecting internet surveys, such as measurement, survey design and sampling selection bias. The sampling has an important place in selection bias in internet survey. In terms of sample selection, the type of access to internet surveys has several limitations. There are internet surveys based on restricted access and on voluntary participation, and these are characterized by their implementation according to the type of survey. It can be used probability and non-probability sampling, both of which may lead to biased estimates. There are different ways to correct for selection biases; poststratification or weighting class adjustments, raking or rim weighting, generalized regression modeling and propensity score adjustments. This paper aims to describe methodological problems about selection bias issues and to give a review in internet surveys. Also the objective of this study is to show the effect of various correction techniques for reducing selection bias.

The effect of different sample sizes on estimation methods such as weighted least squares and robust weighted least squares that are used in structural equation modeling was studied and compared using information criteria such as Akaike Information Criteria in this study. The simulations were repeated 1000 times with two estimation methods and the average values of criteria were calculated with different sample sizes. The study includes a construct of four factors, with four questions of each that are measured on a five-point Likert scale. Different sample sizes, ranging from 300 to 5000 were selected. According to the simulations results, it is concluded that the robust estimation method provides more effective results at lower sample size. In addition, it was found that as the sample size increases, the efficiency difference between two methods gradually decreases. Moreover, it was detected that there is almost no difference between the two methods for sample sizes over 3000.

The aim of this study is to show complementary usage of logistic and correspondence analysis in a research subject to self-healing methodologies. Firstly, the number of the variables is reduced by logistic regression according to relationship between dependent and independent variables and then research carries on searching variables. The relationship among the behaviours of individuals and their demographic characteristics is modelled by logistic regression and shown graphically by correspondence analysis. In application, first of all, the effect of age, sex, marital status, education level, occupation and income level and present health condition, on appreciating selfhealth, is explained by a model. As a result of that model, it can be said that the effect of age, occupation and present health condition is reasonable. After analysing that model, the relationship between categorical variables (age, sex, occupation, preferred precautions, and worth of personal health) is shown graphically by multiple correspondence analysis.

In this age of advanced technology, every university has a website to endorse their programs and encourage students around the world to join one of their faculties. However, universities give less attention to meet the users' demands for visually attractive websites that satisfy their emotions. This study proposes a Kansei Engineering approach based on human emotion to identify elements of website design that are emotionally appealing to 18-37 year-old students in Turkish universities. A total of 22 Kansei words and 9 sample websites of Turkish universities were selected for the study. The sample consisted of 172 students, who were asked to evaluate the selected websites using Kansei words. A five-point semantic differential scale was used to evaluate the relationship between website elements and the Kansei words. The multivariate statistical methods factor analysis and partial least squares regression were used to implement the Kansei approach. The results displayed that Kansei Engineering methodology and multivariate statistical analyses played a key role in designing an attractive website in order to satisfy student's emotions. It also showed that a pleasant university website should have top menu, small header size, logo on the left side and so on.

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Nowadays, doctorate holders are not only academicians and researchers, but they also play roles across a broad ground of working areas within society. These areas are versatile and increasing in way. The aim of this study is to make statistical evaluation of careers of doctorate holders survey using the correspondence analysis with supplementary variables. The focus of this paper is doctorate holders in Turkey. A survey regarding this matter was carried out by Turkish Statistical Institute. This survey includes various questions such as gender, age, employment situation, field of science, etc. Using correspondence analysis we investigated doctorate holders in relation to their gender and employment situation and employment sector. How the employment situation of doctorate holders changes according to gender and year of doctorate award; and doctorate holders' satisfaction level on their principal job by selected title have been shown.