We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
This chapter explains how to design experiments to study black-box corporate surveillance systems. The chapter first examines the kinds of research questions that can be asked about corporate surveillance systems. Then, it describes different high-level study designs for transparency research, followed by a look at longitudinal studies and how they can be conducted. After examining the challenges that transparency researchers face in designing these experiments, the chapter focuses on input variables that are influenced and varied during an experiment, variables that are outside the experimenter's influence, and variables that are measured (response or output variables).
Research design is inextricably linked to data analysis. Research designs can be divided into three fundamental categories: experimental design, quasi-experimental design, and nonexperimental or passive observational design. This chapter focuses almost exclusively on experimental design, for two main reasons. In an experimental design there are always at least two factors such as fixed and random factors or independent variables, variables that are considered to influence the dependent variable response. The chapter discusses a series of questions that must be answered regarding each individual factor in a design. It considers the possible ways that multiple factors included in a single experiment may be interrelated. Multiple factors in a design can be crossed, nested, or confounded. Issues involving the dependent measures in a study are also part of experimental design, and these choices can influence statistical conclusion validity (power), internal validity, construct validity, and external validity.
Recommend this
Email your librarian or administrator to recommend adding this to your organisation's collection.