Overview
BUSI820: Quantitative Research Methods
Stephanie Fisher
May 20 2026
Discussion Forum 1: Variables, Research Questions and Data Coding
D1.1 Active and Attribute Independent Variables
D1.1.a Similarities
As stated by Barrett et al. (2026), both active and attribute independent variables (IVs) have been employed in studies where an IV predicts or explains variance in the dependent variable. The common aspect here is the fact that both are used as independent variables when posing research questions and performing statistics. It is important to distinguish between the two types of variables, as pointed out by William et al. (2024) during a meta-analysis on induced mindfulness (manipulated IV) and dispositional mindfulness (attribute IV).
D1.1.b Differences
It comes down to the fact that the notion of active independent variable implies the manipulation of the values of independent variable by the researcher (as evidenced by the presence of both control and treatment groups), while attribute independent variable refers to an inherent property of subjects under study like their sex or religion, which is not manipulated but measured (Barrett et al., 2026). This point is clarified even further in the work by Kraines et al. (2025), who draw the distinction between trait mindfulness (attribute variable) and mindfulness induction techniques (active variable).
D1.2 Causal Inference and Independent Variables
D1.2.a Type of Independent Variable Necessary for Cause
The existence of an active independent variable is needed to claim causation from the experimental research (Barrett et al., 2026). In this regard, the study conducted by Williams et al. (2024) supports this idea in a systematic literature review, proving that causality of the effectiveness of mindfulness-based interventions can be established only through randomized controlled trials.
D1.2.b Whether Cause Can Always Be Inferred
But, causal inference may not necessarily be based on an active IV alone. Causation may only occur when randomization, the manipulation of the independent variable, the control of the extraneous factors, and evidence of covariance are present (Barrett et al., 2026). According to Kraines et al. (2025), even when properly executed, third variables such as optimism and hope can partly explain the connection between mindfulness and anxiety.
D1.2.c When Causal Inferences Are Justified vs. Questionable
Barrett et al. (2026) argue that when it comes to quasi-experiments without random assignment or when confounding variables exist, making any causal claims becomes less credible even in the case of the existence of a valid IV. The same limitation occurs in the case of an attribute IV like religion because this IV cannot be manipulated and is inherently confounded. Williams et al. (2024) are consistent in their arguments, emphasizing that their meta-analysis included both randomized control studies and quasi-experiments where causal claims could be considered less credible.
D1.3 Difference Between Independent and Dependent Variables
As defined by Barrett et al. (2026), the independent variable (IV) is the presumed cause, predictor, or grouping variable, whereas the dependent variable (DV) is the presumed effect, outcome, or criterion variable. The DV is measured to see ho