Estimating the Causal Effects of Marketing Interventions Using Propensity Score Methodology

Propensity score methods were proposed by Rosenbaum and Rubin [Biometrika 70 (1983) 41--55] as central tools to help assess the causal effects of interventions. Since their introduction more than two decades ago, they have found wide application in a variety of areas, including medical research, economics, epidemiology and education, especially in those situations where randomized experiments are either difficult to perform, or raise ethical questions, or would require extensive delays before answers could be obtained. In the past few years, the number of published applications using propensity score methods to evaluate medical and epidemiological interventions has increased dramatically. Nevertheless, thus far, we believe that there have been few applications of propensity score methods to evaluate marketing interventions (e.g., advertising, promotions), where the tradition is to use generally inappropriate techniques, which focus on the prediction of an outcome from background characteristics and an indicator for the intervention using statistical tools such as least-squares regression, data mining, and so on. With these techniques, an estimated parameter in the model is used to estimate some global ``causal'' effect. This practice can generate grossly incorrect answers that can be self-perpetuating: polishing the Ferraris rather than the Jeeps ``causes'' them to continue to win more races than the Jeeps $\Leftrightarrow$ visiting the high-prescribing doctors rather than the low-prescribing doctors ``causes'' them to continue to write more prescriptions. This presentation will take ``causality'' seriously, not just as a casual concept implying some predictive association in a data set, and will illustrate why propensity score methods are generally superior in practice to the standard predictive approaches for estimating causal effects.Comment: Published at http://dx.doi.org/10.1214/088342306000000259 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Tropical Geometry of Statistical Models

This paper presents a unified mathematical framework for inference in graphical models, building on the observation that graphical models are algebraic varieties. From this geometric viewpoint, observations generated from a model are coordinates of a point in the variety, and the sum-product algorithm is an efficient tool for evaluating specific coordinates. The question addressed here is how the solutions to various inference problems depend on the model parameters. The proposed answer is expressed in terms of tropical algebraic geometry. A key role is played by the Newton polytope of a statistical model. Our results are applied to the hidden Markov model and to the general Markov model on a binary tree.Comment: 14 pages, 3 figures. Major revision. Applications now in companion paper, "Parametric Inference for Biological Sequence Analysis

Testing of improved polyimide actuator rod seals at high temperature and under vacuum conditions for use in advanced aircraft hydraulic systems

Polyimide second-stage rod seals were evaluated to determine their suitability for applications in space station environments. The 6.35-cm (2.5-in.)K-section seal was verified for thermal cycling operation between room temperature and 478 K (400 F) and for operation in a 133 micron PA(0.000001 mm Hg) vacuum environment. The test seal completed the scheduled 96 thermal cycles and 1438 hr in vacuum with external rod seal leakage well within the maximum allowable of two drops per 25 actuation cycles. At program completion, the seals showed no signs of structural degradation. Posttest inspection showed the seals retained a snug fit against the shaft and housing walls, indicating additional wear life capability. Evaluation of a molecular flow section during vacuum testing, to inhibit fluid loss through vaporization, showed it to be beneficial with MIL-H-5606, a petroleum-base fluid, in comparison with MIL-H-83282, a synthetic hydrocarbon-base fluid

Development of the Trident 1 aerodynamic saike mechanism

The Aerospike drag reduction mechanism was designed and developed for use on the Trident I submarine launched ballistic missile. This mechanism encounters a unique combination of environments necessitating unique design solutions to ensure satisfactory operation over its design life. The development of the Aerospike is reviewed emphasizing the unique and interesting problems encountered and their solutions

Parametric Inference for Biological Sequence Analysis

One of the major successes in computational biology has been the unification, using the graphical model formalism, of a multitude of algorithms for annotating and comparing biological sequences. Graphical models that have been applied towards these problems include hidden Markov models for annotation, tree models for phylogenetics, and pair hidden Markov models for alignment. A single algorithm, the sum-product algorithm, solves many of the inference problems associated with different statistical models. This paper introduces the \emph{polytope propagation algorithm} for computing the Newton polytope of an observation from a graphical model. This algorithm is a geometric version of the sum-product algorithm and is used to analyze the parametric behavior of maximum a posteriori inference calculations for graphical models.Comment: 15 pages, 4 figures. See also companion paper "Tropical Geometry of Statistical Models" (q-bio.QM/0311009

Exact solution of the Bernoulli matching model of sequence alignment

Through a series of exact mappings we reinterpret the Bernoulli model of sequence alignment in terms of the discrete-time totally asymmetric exclusion process with backward sequential update and step function initial condition. Using earlier results from the Bethe ansatz we obtain analytically the exact distribution of the length of the longest common subsequence of two sequences of finite lengths $X,Y$. Asymptotic analysis adapted from random matrix theory allows us to derive the thermodynamic limit directly from the finite-size result.Comment: 13 pages, 4 figure

Model for Folding and Aggregation in RNA Secondary Structures

We study the statistical mechanics of RNA secondary structures designed to have an attraction between two different types of structures as a model system for heteropolymer aggregation. The competition between the branching entropy of the secondary structure and the energy gained by pairing drives the RNA to undergo a `temperature independent' second order phase transition from a molten to an aggregated phase'. The aggregated phase thus obtained has a macroscopically large number of contacts between different RNAs. The partition function scaling exponent for this phase is \theta ~ 1/2 and the crossover exponent of the phase transition is \nu ~ 5/3. The relevance of these calculations to the aggregation of biological molecules is discussed.Comment: Revtex, 4 pages; 3 Figures; Final published versio

A RISC-V Vector Processor With Simultaneous-Switching Switched-Capacitor DC-DC Converters in 28 nm FDSOI

This work demonstrates a RISC-V vector microprocessor implemented in 28 nm FDSOI with fully integrated simultaneous-switching switched-capacitor DC-DC (SC DC-DC) converters and adaptive clocking that generates four on-chip voltages between 0.45 and 1 V using only 1.0 V core and 1.8 V IO voltage inputs. The converters achieve high efficiency at the system level by switching simultaneously to avoid charge-sharing losses and by using an adaptive clock to maximize performance for the resulting voltage ripple. Details about the implementation of the DC-DC switches, DC-DC controller, and adaptive clock are provided, and the sources of conversion loss are analyzed based on measured results. This system pushes the capabilities of dynamic voltage scaling by enabling fast transitions (20 ns), simple packaging (no off-chip passives), low area overhead (16%), high conversion efficiency (80%-86%), and high energy efficiency (26.2 DP GFLOPS/W) for mobile devices

Genetic Correlations in Mutation Processes

We study the role of phylogenetic trees on correlations in mutation processes. Generally, correlations decay exponentially with the generation number. We find that two distinct regimes of behavior exist. For mutation rates smaller than a critical rate, the underlying tree morphology is almost irrelevant, while mutation rates higher than this critical rate lead to strong tree-dependent correlations. We show analytically that identical critical behavior underlies all multiple point correlations. This behavior generally characterizes branching processes undergoing mutation.Comment: revtex, 8 pages, 2 fig

Similarity-Detection and Localization

The detection of similarities between long DNA and protein sequences is studied using concepts of statistical physics. It is shown that mutual similarities can be detected by sequence alignment methods only if their amount exceeds a threshold value. The onset of detection is a continuous phase transition which can be viewed as a localization-delocalization transition. The ``fidelity'' of the alignment is the order parameter of that transition; it leads to criteria for the selection of optimal alignment parameters.Comment: 4 pages including 4 figures (308kb post-script file