Categorical/qualitative factor

Table 2.4 shows basic statistical designs for all kinds of quantitative and categorical/qualitative factors. 

Simple comparative designs Categorical/qualitative and quantitative Check of method, testing of single factor effect... 

Fractional replicate designs Categorical/qualitative and quantitative Screening of factors... 

Full factorial designs Categorical / qualitative, quantitative and combined Choice of factors, calculation of main effects and interactions... 

Factor is a controllable variable of interest. The factor can be either quantitative or qualitative. A quantitative factor can be measured on a numerical scale. Some examples of qualitative factors include the temperature of a furnace, amount of a chemical, ratio of a material portion, weight of a snbstrate, etc. A qualitative factor can be categorized into a group. Examples include type of material, suppliers, operators, etc. 

A case of application of fractional replica 27-3 of a full factorial experiment on studying adhesion of thermoplastic polymer and fiber has been analyzed earlier in Example 2.33. Tensile strength of adhesion has been measured as the system response. The experiment included seven factors, with the nature of fiber being a qualitative-categorical factor. The regression coefficient values and method of steepest ascent are shown Table 2.188. 

Simplex optimization is used in extreme experiments where besides quantitative-continuous also qualitative-categorical factors are included. 

An important advantage of two level factorial designs is that some factors can be categorical in nature, that is, they do not need to refer to a quantitative parameter. One factor may be whether a reaction mixture is stirred (+ level) or not (— level), and another whether it is carried out under nitrogen or not. Thus these designs can be used to ask qualitative questions. The values of the b parameters relate directly to the significance or importance of these factors and their interactions. 

KJ Method was named after Jiro Kawakita, a man of many talents who was a professor of cultural anthropology in Japan. After extensive field research in Nepal during the 1960s, Kawakita developed the KJ Method to improve the integration and categorization of qualitative data around such factors as the environment, population, relationships, hierarchy, and religion. 

Although neuroticism is not a disease per se, it predisposes individuals to anxiety disorders (12, 13). Neuroticism is a vulnerability factor for all forms of anxiety (14-16). A system established by the Diagnostic and Statistical Manual for Psychiatric Disorders in the United States, currently in its 4th edition (DSM-IV) text revision (TR) (American Psychiatric Association, 2000), sets the boundary at which a particular level of behavior becomes an anxiety disorder—a level often based on the number and the duration of symptoms. DSM is a categorical system based on the qualitative separation of disease states from the state of well-being. The DSM-IVTR category of anxiety disorders currently includes generalized anxiety disorder (GAD), simple phobia, posttraumatic stress disorder (PTSD), panic disorder, social phobia, and obsessive compulsive disorder (OCD) as discrete anxiety disorders. The International Classification of Diseases-10 (IC-10) is a similar system, but it is less frequently used in research (17). 

There are many ways to categorize safety performance measures. They are often classified as trailing or leading indicators, outcome or process oriented, results or activity-based measures, downstream factors or upstream factors, and/or qualitative or quantitative metrics. 

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