Researchers at Columbia University, Princeton and Harvard University have developed a new approach for analyzing big data that can drastically improve the ability to make accurate predictions about medicine, complex diseases, social science phenomena, and other issues.
In a study published in the December 13 issue of Proceedings of the National Academy of Sciences (PNAS), the authors introduce the Influence score, or “I-score,” as a statistic correlated with how much variables inherently can predict, or “predictivity”, which can consequently be used to identify highly predictive variables.
“In our last paper, we showed that significant variables may not necessarily be predictive, and that good predictors may not appear statistically significant,” said principal investigator Shaw-Hwa Lo, a professor of statistics at Columbia University. “This left us with an important question: how can we find highly predictive variables then, if not through a guideline of statistical significance? In this article, we provide a theoretical framework from which to design good measures of prediction in general. Importantly, we introduce a variable set’s predictivity as a new parameter of interest to estimate, and provide the I-score as a candidate statistic to estimate variable set predictivity.”
Current approaches to prediction generally include using a significance-based criterion for evaluating variables to use in models and evaluating variables and models simultaneously for prediction using cross-validation or independent test data.
“Using the I-score prediction framework allows us to define a novel measure of predictivity based on observed data, which in turn enables assessing variable sets for, preferably high, predictivity,” Lo said, adding that, while intuitively obvious, not enough attention has been paid to the consideration of predictivity as a parameter of interest to estimate. Motivated by the needs of current genome-wide association studies (GWAS), the study authors provide such a discussion.
In the paper, the authors describe the predictivity for a variable set and show that a simple sample estimation of predictivity directly does not provide usable information for the prediction-oriented researcher. They go on to demonstrate that the I-score can be used to compute a measure that asymptotically approaches predictivity. The I-score can effectively differentiate between noisy and predictive variables, Lo explained, making it helpful in variable selection. A further benefit is that while usual approaches require heavy use of cross-validation data or testing data to evaluate the predictors, the I-score approach does not rely as much on this as much.
“We offer simulations and an application of the I-score on real data to demonstrate the statistic’s predictive performance on sample data,” he said. “These show that the I-score can capture highly predictive variable sets, estimates a lower bound for the theoretical correct prediction rate, and correlates well with the out of sample correct rate. We suggest that using the I-score method can aid in finding variable sets with promising prediction rates, however, further research in the avenue of sample-based measures of predictivity is needed.”
The authors conclude that there are many applications for which using the I-score would be useful, for example in formulating predictions about diseases with high dimensional data, such as gene datasets, in the social sciences for text prediction or financial markets predictions; in terrorism, civil war, elections and financial markets.
“We’re hoping to impress upon the scientific community the notion that for those of us who might be interested in predicting an outcome of interest, possibly with rather complex or high dimensional data, we might gain by reconsidering the question as one of how to search for highly predictive variables (or variable sets) and using statistics that measure predictivity to help us identify those variables to then predict well,” Lo said. “For statisticians in particular, we’re hoping this opens up a new field of work that would focus on designing new statistics that measure predictivity.”
Receive an email update when we add a new PREDICTION TOOL article.
The Latest on: Accurate predictions
via Google News
The Latest on: Accurate predictions
- CT team developing suicide prediction algorithmon January 23, 2021 at 9:36 am
Imagine a world in which doctors can predict, with almost perfect accuracy, who is the most at risk for suicide. That world is not too far off.
- UFC 257: Dan Hooker vs. Michael Chandler odds, picks and predictionon January 23, 2021 at 3:11 am
Previewing Saturday’s UFC 257 fight between Dan Hooker and Michael Chandler, with MMA betting odds, picks, tips and predictions.
- UFC 257: Marina Rodriguez vs. Amanda Ribas odds, picks and predictionon January 22, 2021 at 8:23 pm
In a women's strawweight bout on Saturday's main card, Marina Rodriguez and Amanda Ribas meet at UFC 257 at the Etihad Arena in Abu Dhabi, United Arab Emirates. The early prelims and prelims kick off ...
- UFC 257: Jessica Eye vs. Joanne Calderwood odds, picks and predictionon January 22, 2021 at 1:11 pm
Previewing Saturday’s UFC 257 fight between Jessica Eye and Joanne Calderwood, with MMA betting odds, picks, tips and predictions.
- "The Simpsons" yet again made eerily accurate predictions – this time about Inauguration Dayon January 22, 2021 at 11:21 am
Many people couldn't help but draw similarities between Inauguration Day 2021 and the past. No, they weren't comparing it to past presidential inaugurations, but to old scenes in "The Simpsons." The ...
- Bold Predictions for the 2020-21 Dallas Stars Seasonon January 22, 2021 at 6:07 am
Before the start of the 2019-20 season, I decided to make some bold predictions for how the Dallas Stars’ season would turn out. Needless to say, I failed spectacularly (although the Ben Bishop one ...
- Accurate predictions of ovarian cancer outcome possible with new classification systemon January 14, 2021 at 10:38 am
The new, Oxford-developed method for subtyping ovarian cancer has been validated in a recent collaboration between the University of Oxford and Imperial College London. Dubbed the "Oxford Classic," ...
- What is a margin of error? This statistical tool can help you understand vaccine trials and political pollingon January 7, 2021 at 9:00 am
Each of these questions involves some uncertainty, but it is still possible to make accurate predictions as long as that uncertainty is understood. One tool statisticians use to quantify ...
- My 2021 New Year's Resolution and Market Predictionon December 29, 2020 at 9:17 pm
My stock market prediction for 2021 is that there will be several uptrends and downtrends. I have no idea where the S&P 500 will be a year from now or how it will get it there. I also predict that ...
via Bing News