1. L

    Logistic Regression of NFL Data

    Week 5 picks from a logistic regression model for the NFL:
  2. Y

    Statistical/ML models when observations have different amounts of input

    Let's say we're predicting an employee's performance review score for the following year based on that emplyee's metrics from each previous year of his/her employment. We might have these training observations below. Note that "2014i" means "that employee's set of input values from 2014", which...
  3. S

    Betting Statistics - Calculation of odds accuracy - what am I measuring here?

    Hello folks! Before anything, an important disclaimer: I am an amateur at statistics and I’m trying to learn by my own. Please bear with me if the questions below sounds like utter nonsense to you guys: In an experiment where you have Team A playing a game of any sports against Team B, both...
  4. G

    Error band for calibration correction of an instrument

    I apologize if this is the wrong area to post this. It seems like it could fall into a couple different areas. I have a question about calculating the expected error around a calibration curve for an instrument. I have a calibration curve for a load cell. It was measured at a few different...
  5. H

    Regression analysis(?) for multiple independent variables

    Hello all, Apologies for posting an elementary query, but my stats is very rusty. Not looking for an explicit solution, necessarily, just a pointer in the right direction. (And if I've posted to the wrong sub-forum, I'd be grateful for suggestions.) I have N records. Each contains M real...
  6. B

    How do risk models deal with state changes over time?

    Let's say you are trying to predict if a machine is going to explode (0) or successfully complete its job (1), and you are trying to determine the impact of certain states on the machine. So say the machine has state A, B, C, and D. The machine starts in state A. Then... A-> B, B->C *OR*...
  7. T

    One observation per factor level combination in regression

    Hi... I was wondering if you can perform multiple linear regression with a mix of categorical and quantitative variables, if you only have one observation per combination of the levels of your factors in the regression model? And how do you interpret predictions? Thanks in advance!
  8. J

    How to use structural equation modeling (SEM) in prediction tasks?

    Hi all, I have built a SEM model in Amos as attached image. There are five components, and one modulation factor. If I know four of the five components, can I use the model to predict the 5th component? How can I do this? Are there anything like factor score coefficient Matrix (those in...
  9. E

    Using the Multiple Linear Regression Model to predict values.

    I've used R to create two linear regression models - one level-level and one log-level, from 125 lines of data given to me. I've been told: For both of the models I've been told to fit the model using the first 100 rows of the data, and then use the fitted models to predict y from the...
  10. E

    Bayesian regression

    it's a actually an informatics math related question. But i want to start here to get a first opinion. As a software engineer and cryptographer, I'm developing an application to predict to price of certain alt-coin. I have read a paper about the math behind the algorithm. I have a more then...
  11. K

    Predicting the near-future values using an unevenly sampled time-series data

    Hi there, I need help with predicting the near-future values using an unevenly sampled time-series data. Data is collected as events, and is converted to time series. I have tried out a few approached which have not been successful. Please let me know if there is anything I can do around...
  12. D

    Predicting a Finite Sequence of Events

    Hello everyone, I have very little experience with statistics, but I have a general problem that I think it might be applicable to. My primary difficulty is that I'm not familiar enough with the field to know which areas I should be researching. The data I have consist of many ordered...
  13. I

    How to determine the number of items needed to design a reliable test

    An educational assessment form equivalence problem. I produce a large (infinite?) pool of items similar in quality. I administer a test that uses items from the pool. For each testee, items are drawn at random from the pool. The testees respond to x number of items. If I need a reliability...
  14. G

    What analysis to use

    Dear all, I have 3 independent variables (1-5 Likert Scale) questions and I want to check how well these three can predict/explain my DV (1-5 Likert scale) The three independent variables are: 1. Quality of information 2. Accessibility of staff 3. Quality of technical advice My DV...
  15. M

    Prediction using Support Vector (SV) method

    Dear Friends, I came to know that using SVM method we can predict the future value more accurately than other normal methods (like ARIMA). My question is how do we give the future index value (let's say 101 when we have 100 values in a time series) so that we can get the predicted value for the...
  16. M

    Prediction using Support Vector (SV) method in R

    Dear Friends, I came to know that using SVM method we can predict the future value more accurately than other normal methods (like ARIMA). My question is how do we give the future index value (let's say 101 when we have 100 values in a time series) so that we can get the predicted value for...
  17. E

    Quantile prediction?

    Here is my situation. I am trying to predict the 'entire' distribution of the dependent variable, not just the mean( or conditional mean). Does it then make sense to seprateley predict quantiles of this variable to learn about the new predicted CDF? I intend to use this CDF as one input (say...
  18. M

    Alternatives for logistic regression?

    Hey everyone! I need some help because I am not really happy with the data analysis for my thesis. I am investigating the prognostic power of 3 quantitative and 2 qualitative variable on a dichotomous outcome. First off I wanted to know which set of variables is the best to predict the...
  19. S

    Good model for association of for prediction?

    Hello everybody, I have a "conceptual issue": I have been told that the program that performs best in finding a lot of feature associated to a phenotype of interest will not perform best for predicting the phenotype of interest out of the features, and vice-versa. I do not quite understand...
  20. I

    Is it appropriate to include intermediate outcomes in a predictive model?

    It is quite clear that one should not control for post-treatment variables / intermediate outcomes when the goal is causal inference, but I wasn't sure if the same advice should hold when one's goal is to build a model for prediction. Context for my question: I'm trying to build a model that...