Search Results

Search found 3 results on 1 pages for 'race1'.

Page 1/1 | 1 

• R glm standard error estimate differences to SAS PROC GENMOD

  - by Michelle

  I am converting a SAS PROC GENMOD example into R, using glm in R. The SAS code was: proc genmod data=data0 namelen=30; model boxcoxy=boxcoxxy ~ AGEGRP4 + AGEGRP5 + AGEGRP6 + AGEGRP7 + AGEGRP8 + RACE1 + RACE3 + WEEKEND + SEQ/dist=normal; FREQ REPLICATE_VAR; run; My R code is: parmsg2 <- glm(boxcoxxy ~ AGEGRP4 + AGEGRP5 + AGEGRP6 + AGEGRP7 + AGEGRP8 + RACE1 + RACE3 + WEEKEND + SEQ , data=data0, family=gaussian, weights = REPLICATE_VAR) When I use summary(parmsg2) I get the same coefficient estimates as in SAS, but my standard errors are wildly different. The summary output from SAS is: Name df Estimate StdErr LowerWaldCL UpperWaldCL ChiSq ProbChiSq Intercept 1 6.5007436 .00078884 6.4991975 6.5022897 67911982 0 agegrp4 1 .64607262 .00105425 .64400633 .64813891 375556.79 0 agegrp5 1 .4191395 .00089722 .41738099 .42089802 218233.76 0 agegrp6 1 -.22518765 .00083118 -.22681672 -.22355857 73401.113 0 agegrp7 1 -1.7445189 .00087569 -1.7462352 -1.7428026 3968762.2 0 agegrp8 1 -2.2908855 .00109766 -2.2930369 -2.2887342 4355849.4 0 race1 1 -.13454883 .00080672 -.13612997 -.13296769 27817.29 0 race3 1 -.20607036 .00070966 -.20746127 -.20467944 84319.131 0 weekend 1 .0327884 .00044731 .0319117 .03366511 5373.1931 0 seq2 1 -.47509583 .00047337 -.47602363 -.47416804 1007291.3 0 Scale 1 2.9328613 .00015586 2.9325559 2.9331668 -127 The summary output from R is: Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 6.50074 0.10354 62.785 < 2e-16 AGEGRP4 0.64607 0.13838 4.669 3.07e-06 AGEGRP5 0.41914 0.11776 3.559 0.000374 AGEGRP6 -0.22519 0.10910 -2.064 0.039031 AGEGRP7 -1.74452 0.11494 -15.178 < 2e-16 AGEGRP8 -2.29089 0.14407 -15.901 < 2e-16 RACE1 -0.13455 0.10589 -1.271 0.203865 RACE3 -0.20607 0.09315 -2.212 0.026967 WEEKEND 0.03279 0.05871 0.558 0.576535 SEQ -0.47510 0.06213 -7.646 2.25e-14 The importance of the difference in the standard errors is that the SAS coefficients are all statistically significant, but the RACE1 and WEEKEND coefficients in the R output are not. I have found a formula to calculate the Wald confidence intervals in R, but this is pointless given the difference in the standard errors, as I will not get the same results. Apparently SAS uses a ridge-stabilized Newton-Raphson algorithm for its estimates, which are ML. The information I read about the glm function in R is that the results should be equivalent to ML. What can I do to change my estimation procedure in R so that I get the equivalent coefficents and standard error estimates that were produced in SAS? To update, thanks to Spacedman's answer, I used weights because the data are from individuals in a dietary survey, and REPLICATE_VAR is a balanced repeated replication weight, that is an integer (and quite large, in the order of 1000s or 10000s). The website that describes the weight is here. I don't know why the FREQ rather than the WEIGHT command was used in SAS. I will now test by expanding the number of observations using REPLICATE_VAR and rerunning the analysis.

  Read the article

• matplotlib - write TeX on Qt form

  - by race1

  I'd like to add some TeX text to my Qt form, like label - just text, no graph, no lines, no borders, just TeX. I thought something like this: render TeX to bitmap and then place that bitmap on form, e.g. into QLabel. Or even better - use some backend, add it to form and use something tex_label.print_tex(<tex code>). Seems matplotplot has TeX parsers, but I can't figure out how to use them... Thanks.

  Read the article

• error in a pygame code

  - by mekasperasky

  # INTIALISATION import pygame, math, sys from pygame.locals import * screen = pygame.display.set_mode((1024, 768)) car = pygame.image.load('car.png') clock = pygame.time.Clock() k_up = k_down = k_left = k_right = 0 speed = direction = 0 position = (100, 100) TURN_SPEED = 5 ACCELERATION = 2 MAX_FORWARD_SPEED = 10 MAX_REVERSE_SPEED = ­5 BLACK = (0,0,0) while 1: # USER INPUT clock.tick(30) for event in pygame.event.get(): if not hasattr(event, 'key'): continue down = event.type == KEYDOWN # key down or up? if event.key == K_RIGHT: k_right = down * ­5 elif event.key == K_LEFT: k_left = down * 5 elif event.key == K_UP: k_up = down * 2 elif event.key == K_DOWN: k_down = down * ­2 elif event.key == K_ESCAPE: sys.exit(0) # quit the game screen.fill(BLACK) # SIMULATION # .. new speed and direction based on acceleration and turn speed += (k_up + k_down) if speed > MAX_FORWARD_SPEED: speed = MAX_FORWARD_SPEED if speed < MAX_REVERSE_SPEED: speed = MAX_REVERSE_SPEED direction += (k_right + k_left) # .. new position based on current position, speed and direction x, y = position rad = direction * math.pi / 180 x += ­speed*math.sin(rad) y += ­speed*math.cos(rad) position = (x, y) # RENDERING # .. rotate the car image for direction rotated = pygame.transform.rotate(car, direction) # .. position the car on screen rect = rotated.get_rect() rect.center = position # .. render the car to screen screen.blit(rotated, rect) pygame.display.flip() enter code here the error i get is this Non-ASCII character '\xc2' in file race1.py on line 13, but no encoding declared; see http://www.python.org/peps/pep-0263.html for details Not able to understand what the error is and how to get rid of it?

  Read the article

1