Inter experiment conditions

When designing experiments, especially in psychological and behavioral research, between-group designs are commonplace. These designs involve comparing two or more groups, with each group experiencing a different condition. Cognition has integrated tools to efficiently manage these inter-experiment conditions. Let's delve into how you can utilize this feature:

1. The Essence of Between-Group Study Design

In between-group (or between-groups) designs, different participants are assigned to different conditions, ensuring that each group experiences only one of the conditions.

2. Automatic Participant Assignment

Cognition streamlines the condition assignment process by:

• Automatically allocating participants to different conditions.

• If you specify multiple conditions, Cognition will ensure an even distribution of participants across these conditions. This balance ensures unbiased results and easier statistical analysis.

3. Accessing Assigned Condition in Runtime

Once a participant is assigned to a condition, this information is made available during the experiment runtime via the variable CONDITION.

4. Practical Application

Let's explore a practical code example to understand how CONDITION can be harnessed:

var test_stimuli = [
    { stimulus: "img/blue.png", correct_response: CONDITION == 2 ? 'f' : 'j' },
    { stimulus: "img/orange.png", correct_response: CONDITION == 2 ? 'j' : 'f' }
];

In this scenario:

• If a participant has been assigned to Condition 2, their correct responses will be 'f' for the blue image and 'j' for the orange image.

• For participants in any other condition, the correct responses are reversed.

5. Testing Specific Conditions

While editing your task and using the live preview function:

• Cognition provides an option titled "Set condition."

• This tool allows you to simulate a specific condition, ensuring you can test the task as if you were a participant assigned to that condition.

6. Set Specific Condition Using URL Query Parameters

In addition to the automatic condition assignment feature, Cognition offers flexibility in allowing researchers to set specific conditions using URL query parameters. By appending the query parameter condition to the experiment URL, researchers can bypass the auto-balancing algorithm and ensure that a participant sees a specific version of the experiment.

For example, if you append ?condition=2 to the experiment URL, the participant will be assigned to Condition 2 regardless of the auto-balancing logic. This feature is particularly useful for researchers who wish to control the version seen by specific participants, allowing for more targeted experimentation.

7. Pros of Using Conditions vs. Creating Multiple Tasks

When designing experiments with between-group study designs, researchers often face the decision of whether to use conditions within a single task or create multiple tasks. Each approach has its own set of advantages and disadvantages:

Pros of Using Conditions:

• Single Unique URL: With conditions, researchers only need to manage a single unique URL for the experiment, simplifying participant recruitment and sharing.

• Auto-Balancing: Cognition's auto-balancing system ensures an even distribution of participants across conditions, leading to more reliable and unbiased results.

• Easy Maintenance: Managing a single task with conditions is more straightforward and requires less maintenance compared to managing multiple tasks.

In conclusion, the inter-experiment conditions feature in Cognition greatly simplifies the process of managing and implementing between-group study designs. Whether you're comparing two conditions or several, Cognition ensures a balanced and efficient distribution of participants, all while giving you the tools to easily craft and test condition-specific task elements.