About SpanishPhD

SpanishPhD · ‎08-24-2015

I'm sorry but I can not understand how this works. In my case it is an interaction between a continuous and categorical variable, and I also used proc GLIMMIX with dist= binomial link=logit. Although the method could be similar (continuous*continuous), it is difficult to understand because my little knowledge in SAS. In my particular model, what should I use? Thank you very much, Jaime

SpanishPhD · ‎08-24-2015

Hello, I'm sorry to use this section to my own interest. But I have the same question and I can not find the right command ... This is my model on avian reproduction. Where age1 is a continuous variable(1, 2, 3) and sex is categorical (1= male, 2= female). proc glimmix data=Reproduction INFOCRIT=PQ noreml; class Sex nest Age2 ring; model Reproduction (Event="1") = Sex Age1 Sex*Age1/dist= binomial link=logit solution cl; random Age2/ subject=ring (nest) type=cs residual; ESTIMATE 'sex 1 vs 2 at age 1 in' sex -1 1 0 Sex*Age1 -1 1 0 ; ESTIMATE 'sex 1 vs 2 at age 2 in' sex -1 1 0 Sex*Age1 -2 2 0 ; ESTIMATE 'sex 1 vs 2 at age 3 in' sex -1 1 0 Sex*Age1 -3 3 0 ; run; Could you tell me the correct command to see estimates of the interaction "Sex*Age1"? The estimates that I have shown in my model, showed me only sex differences for each age, but I need male differences along age. I'm sorry for my limited knowledge of SAS. Thank you very much. All the best, Jaime

SpanishPhD · ‎08-23-2015

Thank you very much! In case of not getting the model residuals, I would not integrating the effect of "size". Then... Would it be correct to use only raw data to examine the results graphically without taking into account other significant covariates? Best whishes, Jaime

SpanishPhD · ‎08-21-2015

Hello everyone, This is my final survival model for a bird breeding colony, and I would take the residuals. I know that in proc mixed I must write "/outp=" just behind the model, but I do not know what should I use in proc glimmix. proc glimmix data=Survival INFOCRIT=PQ noreml; class treartment attempt year nest ring; model Survival = treatment Year attempt Treatment*attempt size/ dist= binomial link=logit solution cl; random Year/ subject=ring(nest) type=Cs residual; lsmeans treatment; run; Thanks very much for your help. Best wishes, Jaime

SpanishPhD · ‎01-21-2015

On the other hand, Would it be correct also use this other model? proc genmod data=Vips descending; class year treat sex; model presence = treat Sex year....... / dist = binomial link = logit; run; Thank you very much, Jaime

SpanishPhD · ‎01-21-2015

Proc logistic data=Vips descending; Class treat Sex event year; model presence (Event='1')= treat Sex treat*Sex year treat*weight event*treat weight*event weight*treat*event sex*event sex*event*treat weight event; lsmeans treat Sex treat*Sex year treat*Sex/ilink oddsratio; run; Sistema SAS Procedimiento LOGISTIC Conjunto de datos WORK.VIPS Variable de respuesta presence Número de niveles de respuesta 2 Modelo logit binario Técnica de optimización Puntuación de Fisher Número de observaciones leí 3330 Número de observaciones usa 3213 1 1 463 2 0 2750 La probabilidad modelada es presence =1. Note: 117 observations were deleted due to missing values for the response or explanatory variables. Treat 0 1 1 -1 Sex 1 1 2 -1 event 1 1 0 2 0 1 3 -1 -1 year 2012 1 0 2013 0 1 2014 -1 -1 Criterio de convergencia (GCONV=1E-8) satisfecho. AIC 2651.701 2517.243 SC 2657.776 2638.742 -2 LOG L 2649.701 2477.243 Ratio de verosim 172.4584 19 <.0001 Puntuación 160.0191 19 <.0001 Wald 148.2303 19 <.0001 Treat 1 13.5012 0.0002 Sex 1 5.2251 0.0223 Treat*Sex 1 0.3069 0.5796 year 2 85.8229 <.0001 weight*Treat 1 13.6287 0.0002 Treat*event 2 18.1990 0.0001 weight*event 2 7.5996 0.0224 weight*treat*event 2 16.6071 0.0002 Sex*event 2 1.4899 0.4748 Treat*Sex*weight 2 9.9884 0.0068 weight 1 16.2378 <.0001 event 2 7.5174 0.0233 Intercept 1 -4.3347 0.6141 49.8221 <.0001 Treat 0 1 -2.2545 0.6136 13.5012 0.0002 Sex 1 1 0.1430 0.0626 5.2251 0.0223 Treat*Sex 0 1 1 -0.0346 0.0625 0.3069 0.5796 year 2012 1 0.6182 0.0699 78.1565 <.0001 year 2013 1 -0.00655 0.0759 0.0075 0.9312 weight*Treat 0 1 0.0350 0.00948 13.6287 0.0002 treat*event 0 1 1 0.1580 0.7670 0.0424 0.8368 treat*event 0 2 1 -3.5230 1.0052 12.2831 0.0005 weight*event 1 1 -0.0236 0.0116 4.1426 0.0418 weight*event 2 1 -0.00398 0.0156 0.0647 0.7993 weight*treat*event 0 1 1 -0.00515 0.0116 0.1972 0.6570 weight*treat*event 0 2 1 0.0547 0.0156 12.2368 0.0005 Sex*event 1 1 1 -0.0194 0.0746 0.0678 0.7945 Sex*event 1 2 1 0.1158 0.1027 1.2701 0.2597 Trt1*Sex*event 0 1 1 1 -0.0274 0.0746 0.1350 0.7133 Trt1*Sex*event 0 1 2 1 -0.2429 0.1027 5.5896 0.0181 weight 1 0.0382 0.00948 16.2378 <.0001 event 1 1 1.5374 0.7670 4.0181 0.0450 event 2 1 0.2637 1.0050 0.0689 0.7930 year 2012 vs 2014 3.421 2.615 4.475 year 2013 vs 2014 1.831 1.375 2.439 Concordancia de porcentaje 68.3 D de Somers 0.372 Discordancia de porcentaje 31.1 Gamma 0.374 Porcentaje ligado 0.6 Tau-a 0.092 Pares 1273250 c 0.686

SpanishPhD · ‎01-20-2015

If I change the 1 by 0 in the model statement, the result is the same. Instead of considering the recruitment, calculates the probability of not recruiting. But I mean I found the opposite effect of treatment if I make the graphics from raw data, that if I perform them with SAS. Hence I ask myself if a new word was needed or just left over a word in the script. Thank you very much, Best wishes, Jaime

SpanishPhD · ‎01-19-2015

Your scripts were very useful. However, I think something changes the sign that directs the results when comparing the results obtained with the original data... Could it be possible? Should I add or remove a word in the script? Thank you very much again for your help, Best wishes, Jaime

SpanishPhD · ‎01-19-2015

Thank you very much for your useful assistance!! All the best, Jaime

SpanishPhD · ‎01-16-2015

The years are presence (1) and absence (0) of birds. I really want to know if treatment had effects in the bird recruitment (for each year and in global). For example, I would like say that treatment 1 increased the recruitment in 2011 relative to control. It is part of my database: Bird Treatment Sex Presence_2011 Presence_2012 Presence_2013 Presence_Global weight 353701 0 2 0 0 0 0 56 353702 0 2 1 1 1 1 39 353703 0 2 1 0 0 1 54 353704 0 2 0 0 1 1 63 353705 1 1 0 0 1 1 60 353706 1 1 1 1 0 1 45 353707 1 1 0 1 0 1 52 353708 1 1 0 0 0 0 49 353709 1 1 0 0 1 1 38 Thank you very much All the best; Jaime Muriel

SpanishPhD · ‎01-16-2015

Hello everyone, I have a question about the necessary scripts to make a recruitment analysis in avian studies. What script could you recommend me? Would it be correct? Proc Logistic data=Birds descending; Class treatment Sex; model Presence_2011 (Event='1')= treatment Sex treatment*Sex weight; run; Where for example Variables = Presence in 2011, 2012, 2013, sex, treatment, weight of chick ... Would it be necessary to add more commands? Thank you very much for your time Jaime

SpanishPhD · ‎10-27-2014

Thank you very much. I'll keep that in mind. Yes, I would like to know the estimates of the interactions, since I have found a significant effect in all these interactions. But I'm very confused with the values that I must write in the syntax of SAS based on the levels of the factors. Thank you very much for your great help. All the best, Jaime

SpanishPhD · ‎10-27-2014

Dear SAS users, I'm doing my first analysis with SAS. But I can not go forward because of a simple question ... How could I get the estimates of interactions? For example, in this simple model, where treatment (Trt) is a continuous variable because they are different doses (0 or control 1, 2, 3), age (1, 2, 3 and 4) and Sex (Female Male) are factors . And I want to analyze the quadratic effect of treatment on the size of a bird. My final model would be this (for a repeated measures analysis): proc mixed data = Birds covtest; class Sex Age nest ring; model Size = Trt*Trt*Age Trt*Trt Trt*Age Trt Age Sex Age*Sex / ddfm=satterth; random nest; Repeated age1 / subject = ring (nest) type = ar (1); estimate 'treatment' Trt 1; estimate 'treatment2' Trt*trt 1; estimate 'sex' sex 1 -1; estimate 'Age' 1 1 -1 -1; ????? is it ok? estimate 'Age*Trt' Age*Trt?????????? estimate 'Age*Sex' Age*Sex ?????????? estimate 'trt*trt*Age' trt*trt*Age ????????? run; Thank you very much. All the best, Jaime

SpanishPhD · ‎02-15-2013

Thakns a lot!!! I will try it!!

SpanishPhD · ‎02-15-2013

but this option does not allow me to work with random, do it?

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