24.05.2019

Time-Normalized Yield: A Natural Unit for Effect Size in Anomalies Experiments

Authors: Nelson R.D. Journal: Journal of Scientific Exploration Publication date: 2006 Keywords: effect size, random event generator, random number, REG, RNG, normalization, inter, experiment comparison, meta-analysis, statistics, experimental yields, bits, trials, time normalization
Journal of Scientific Exploration

Comparing the yields in different anomalies experiments is important for both theoretical and practical purposes, but it is problematic because the effects may be measured on differing scales. The units in which experiments are posed vary across digital and analog measures recorded in a wide range of uniquely defined trials, runs, and series. Even apparently fundamental units such as bit rates may lead to disparate calculated effect sizes and potentially misleading inter-experiment comparisons. This paper seeks to identify a study unit that can render the results from various types of anomalies experiments on a common scale. Across several databases generated in the
consistent environment of the Princeton Engineering Anomalies Research (PEAR) laboratory, yield per unit of time is the most promising of several measures considered. The number of hours during which participants attempt to produce anomalous effects can be consistently defined, and the timenormalized yield Y(h) = Z ldhours is demonstrably similar across a number of humanlmachine experiments, with a magnitude of about 0.2. On both practical and heuristic grounds, this constitutes a prima facie case for regarding the timenormalized yield as a natural metric for anomalous effects of consciousness. Application to a broad range of experiments, including examples from other laboratories, confirms the viability and utility of a time-based yield calculation. A X2 test across 12 local and remote databases from PEAR’S humanlmachine experiments indicates strong homogeneity. Inclusion of the remote perception database, which has a significantly larger yield at Y(h) = 0.6, immediately
renders the distribution of effect sizes heterogeneous. These and other applications return reasonable and instructive results that recommend the simple, time-normalized yield as a natural unit for cross-experiment comparisons permitting an integrated view of anomalies research results.

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