Variables free-text

The problem for the statistical programmer in categorizing data comes from text variables, or more specifically, free-text variables. A free-text variable is one that may contain any characters and is typically limited only in length. As an example, let s say you need to summarize the adverse events for a set of patients in a trial. The following SAS code shows the data and a quick summarization of the adverse events. 

There is only one good solution to handling free-text variables that are needed for statistical analysis. The free-text variables need to be coded by clinical data management in the clinical database. If the adverse events were coded with a dictionary such as MedDRA, the previous example might look like Program 2.3. 

In summary, for data to be useful in clinical trial analyses they need to be quantifiable. The data must be either a continuous measure or a categorical value. Free text poses a problem for analysis, and if it is a valuable variable for the statistical analyses it really must be coded. Finally, hardcoding should be used only when absolutely necessary, because it is inherently problematic. Organizations that do allow hardcoding should document in their standard operating procedures (SOPs) that it is an approved business practice and how it is to be used. 

The adverse event form is fairly standard across clinical trials. The form consists of a list of events for which data are entered as free text and are later coded with a dictionary such as MedDRA and some associated event attribute variables. In just about any clinical trial, an adverse event form very similar to the following sample will be found. 

In this appendix we provide the generalized equations for the mean-field potential and double layer interaction free energy between two surfaces having distinct but periodic nonuniform distributions. These results were taken from Ref. [78]. We denote by yL(s) the charge distribution on the left (L) surface at z = 0 and yR(s) that on the right (R) surface at z — h. As in the text the variable y represents either surface potential, T (s), or surface charge, periodic distribution represented by the Fourier expansions,... 

The free energy relationships involving concentration variables differ from the normal ones in that they give information only about stoichiometry and not about the charge structure of the transition state of a reaction. The topic is very extensive and for this reason we refer the reader to more advanced texts and references for further information. 

In his 1986 text Aitchison proves (for the mathematically literate reader) that die covariance structure of log-ratios is superior to the covariance structure of a percentage array (the crude covariance structure, as it is termed in his text). The covariance structure of log-ratios is free from the problems of the negative bias and of subcompositions which bedevil percentage data. In detail he shows that there are three ways in which the compositional covariance structure can be specified. Each is illustrated in Table 2.5. Firsdy, it can be presented as a variation matrix in which the log-ratio variances are plotted for every variable ratioed to every other variable. This matrix provides a measure of the relative variation of every pair of variables and can be used in a descriptive sense to identify relationships within the data array and in a comparative mode between data arrays. 

Since the 1960s position annihilation lifetime spectroscopy (PALS) has been used to measure free-volume cell size and/or its content in liquids or solids. The three chapters of Part III discuss correlations between the PALS experimental values and those computed from the S-S theory. Chapter 10, by Consolati and Quasso, considers free volume in amorphous polymers Chapter 11, by Dlubek, its distribution from PALS and Chapter 12, by Jamieson et al., the free volume in heterogeneous polymer systems. These state of the art texts offer intriguing observations on the structure of polymeric systems and its variation with independent variables. In all cases, good correlation has been found between the free-volume quantity measured by PALS and its variability computed from the S-S equation of state. 

As mentioned in the preceding text, free energy of adsorption of ions or molecules, and, correspondingly, the value of lny3 (see Eq. 35) depends on one of electrical variables electrode potential E, electrode... 

The thermodynamics of the pyroelectric effect has been already described in Table 4.1 in general. We try to explain this phenomenon more in details in following text. Let ITS choose the independent variables - temperature , electric field Ek and mechanical stress T. Bormdary conditions of the mechanically free sample with shortened electrodes are assumed for constant electric field and mechanical stress. The equations of state for the electric displacement reduce to... 

A schematic representation of a gas frozen in time with indication of the velocity vectors is shown in Fig. 1.8. It is now rather easy to derive an equation, the ideal gas law, that links the microscopic model with the macroscopically measurable variables pressure, p, volume, V, temperature, T, and number of moles, n [Eq. (1), for derivations see any freshman chemistry or physical chemistry text]. The constant R is the universal gar constant its value is 8.3143 J K 1 mol l. The left half of the relationship was first derived by experiment using purely macroscopic tools. The curve at temperature T in the bottom graph of Fig. 1.8 represents such an experiment. microscopic model of a gas reveals now that pV is also equal to /2>)Nmv the right half of Eq. (1). This equation easily achieves a connection between the macroscopic parameters p, V, n, and T and the microscopic parameters N, m, and v Actually, the volume V is also a microscopic parameter, since it tells the space in which the molecules are free to move. 

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