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  • Eligibility criteria: fraud prevention methods that work

    Article by Ben Howell

    Photo by Pixabay from Pexels

    Detect and prevent fraudulent participants from ruining your research by employing these simple, actionable techniques backed up by science.

  • 51 places to find research participants for your study

    Article by Ben Howell

    Photo by Mike from Pexels

    There are many ways to find the participant pools we need, from specialized services to social media, and even (gasp!) in person. By implementing a few different techniques and sampling from different pools, we can recruit participants with much more diverse demographics and surpass minimal sample sizes to provide statistical power to our research. Some methods might be perfectly suitable for a particular study whilst others could be absurdly ludicrous.

  • Online psychology experiments: everything you need to know

    Article by Ben Howell

    Photo by rawpixel.com from Pexels

    Achieve better data quality, better statistical power, and reduce fraudulent behavior in research surveys and psychology experiments by using proven techniques from the scientific literature.

  • Learn research design notation in 2 minutes

    Article by Ben Howell

    Research design notation (sometimes referred to as experimental design notation) is a succinct notation scheme for describing research designs, participant group assignment and experiment flow. Despite its simplicity, it tends to scale well and can easily describe complex experiment designs, making it particularly useful for discussing with colleagues, presenting to a class, and reasoning about your own designs.

  • Online experiments and inaccurate timing. Are we doomed?

    Article by Ben Howell

    Photo by Anton Makarenko from Pexels

    We all want accurate timing for our online psychology experiments, but there are many hardware and software induced confounds that reduce the accuracy of scheduled events and reaction time measurements. To our chagrin, timing in our experiments is not as accurate as we would like, so it seems we're doomed. Or are we? In almost every case, the answer is no.

  • Stimulus Onset Asynchrony (SOA)

    Article by Ben Howell

    Figure 1. Stimulus Onset Asynchrony

    In experimental psychology, Stimulus Onset Asynchrony is defined as the duration of time between the onset of one stimulus and the onset of another stimulus. In (Figure 1) the duration between the onset of the stimulus S1 and the onset of the stimulus S2 is the Stimulus Onset Asynchrony (SOA) interval. Stimulus Onset Asynchrony manipulation is sometimes used as an experimental factor in temporal order judgement experiments.

  • Interstimulus Interval (ISI)

    Article by Ben Howell

    Figure 1. Interstimulus Interval

    Interstimulus Interval is defined as the duration of time between the offset of one stimulus and the onset of another stimulus. In (Figure 1) the duration between the offset of the stimulus S1 and onset of the stimulus S2 is the Interstimulus Interval. Interstimulus Intervals are commonly used as an experimental factor in priming experiments.

  • Intertrial Interval (ITI)

    Article by Ben Howell

    Figure 1. Intertrial Interval

    Intertrial Interval is defined as the duration of time between the onset of one trial and the onset of the next trial. In (Figure 1) the duration between the onset of the stimulus S1 in trial T1and onset of the stimulus S1 in the next trial T2 is the Intertrial Interval. The ITI therefore measures the entire duration from the start of one trial to the start of the next trial, including the duration of fixations, stimuli, responses and the like. Intertrial Intervals are commonly used as an experimental factor in classical conditioning experiments.