Medical Statistics

A Guide to SPSS, Data Analysis and Critical Appraisal

Belinda Barton, Jennifer Peat

• Éditeur: BMJ Books
• Année: 2014
• ISBN:
  9781118589922
• Édition: 2
• Sujet: Medizin
• Sous-sujet: Biostatistik

Medical Statistics provides the necessary statistical tools to enable researchers to undertake and understand evidence-based clinical research.

It is a practical guide to conducting statistical research and interpreting statistics in the context of how the participants were recruited, how the study was designed, what types of variables were used, what effect size was found, and what the P values mean. It guides researchers through the process of selecting the correct statistics and show how to best report results for presentation and publication.

Clear and concise explanations, combined with plenty of examples and tabulated explanations are based on the authors' popular medical statistics courses.

The table of contents is divided into sections according to whether data are continuous or categorical in nature as this distinction is fundamental to selecting the correct statistics. Each chapter provides a clear step-by-step guide to each statistical test with practical instructions on how to generate and interpret the numbers, and present the results as scientific tables or graphs. The chapters conclude with critical appraisal guidelines to help researchers review the reporting of results from each type of statistical test.

This new edition includes a new chapter on repeated measures and mixed models and ahelpful glossary of terms provides an easy reference that applies to all chapters.

Chapter 1
Creating an SPSS data file and preparing to analyse the data

There are two kinds of statistics, the kind you look up and the kind you make up.

REX STOUT

---

Objectives

The objectives of this chapter are to explain how to:

• create an SPSS data file that will facilitate straightforward statistical analyses
• ensure data quality
• manage missing data points
• move data and output between electronic spreadsheets
• manipulate data files and variables
• devise a data management plan
• select the correct statistical test
• critically appraise the quality of reported data analyses

---

1.1 Creating an SPSS data file

Creating a data file in SPSS and entering the data is a relatively simple process. In the SPSS window located on the top left-hand side of the screen is a menu bar with headings and drop-down options. A new file can be opened using the File → New → Data commands located on the top left-hand side of the screen. The SPSS IBM Statistics Data Editor has two different screens called the ‘Data View’ and ‘Variable View’. You can easily move between the two views by clicking on the tabs located at the bottom left-hand side of the screen.

1.1.1 Variable View screen

Before entering data in Data View, the features or attributes of each variable need to be defined in Variable View. In this screen, details of the variable names, variable types and labels are stored. Each row in Variable View represents a new variable and each column represents a feature of the variable such as type (e.g. numeric, dot, string, etc.) and measure (scale, ordinal or nominal). To enter a variable name, simply type the name into the first field and default settings will appear for almost all of the remaining fields, except for Label and Measure.

The Tab, arrow keys or mouse can be used to move across the fields and change the default settings. In Variable View, the settings can be changed by a single click on the cell and then pulling down the drop box option that appears when you double click on the domino on the right-hand side of the cell. The first variable in a data set is usually a unique identification code or a number for each participant. This variable is invaluable for selecting or tracking particular participants during the data analysis process.

Unlike data in Excel spreadsheets, it is not possible to hide rows or columns in either Variable View or Data View in SPSS and therefore, the order of variables in the spreadsheet should be considered before the data are entered. The default setting for the lists of variables in the drop-down boxes that are used when running the statistical analyses are in the same order as the spreadsheet. It can be more efficient to place variables that are likely to be used most often at the beginning of the spreadsheet and variables that are going to be used less often at the end.

Variable names

Each variable name must be unique and must begin with an alphabetic character. Variable names are entered in the column titled Name displayed in Variable View. The names of variables may be up to 64 characters long and may contain letters, numbers and some non-punctuation symbols but should not end in an underscore or a full stop. Variable names cannot contain spaces although words can be separated with an underscore. Some symbols such as @, # or $ can be used in variable names but other symbols such as %, > and punctuation marks are not accepted. SPSS is case sensitive so capital and lower case letters can be used.

Variable type

In medical statistics, the most common types of data are numeric and string. Numeric refers to variables that are recorded as numbers, for example, 1, 115, 2013 and is the default setting in Variable View. String refers to variables that are recorded as a combination of letters and numbers, or j...