The most frequent phrases used concerned scientific issues (1,274 phrases), including research design and methods, presentation and interpretation of results, analysis methods, population studied, power and sample size, measurement variables and measures used, the need for additional data, generalizability, quality of the data, and conflict of interest/ethics [see Table 2].
Due to the nonlinear relationship between measurement variables and state variables, it is difficult to have an analytical solution.
The standardized factor loadings and t-values for measurement variables, and results of CFAs to test measurement models for each construct separately using the AMOS program, are presented in Table 3.
We review a few issues related to clinical trials for treating patients with tinnitus, including the study population, design, choice of measurement variables, and some new approaches to data analysis.
Associations between measurement variables and intention to undergo Pap testing were analysed using correlation analysis.
This can be linked to the generally low levels of correlation (loadings) between the measurement variables and their constructs.
We used stepwise multivariate logistic regression analysis when we had one nominal variable and two or more measurement variables, and we wanted to know how the measurement variables affected the nominal variable and to understand the functional relationship between the independent variables and the dependent variable, to try to understand the likely cause of the change in the dependent variable.
The descriptive analysis was conducted, and the mean and standard deviation were used to describe the measurement variables, and the frequency distribution was used to describe the categorical variable.
Using a framework in quality of life research is important because it promotes the selection of appropriate measurement variables and identifies potential links between variables within the complex construct of quality of life.
To facilitate further data analysis, we assumed a total score of 3 to 6 to indicate low SES, 7 to 11 for middle-level SES, and 12 to 15 for high SES.> To test the statistical significance between groups, t-test was used for measurement variables and chi-square test was used for categorical variables.
Student's t-test was performed to evaluate preoperative to postoperative changes based on radiographic measurements variables (vertebral and local kyphosis and Beck's index).
